Network Optimization

Mathematics & StatisticsAvailable PhD projects

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To complete an application to study, go to the University's application page.

The goal of this project is to explore fundamental structural questions concerning sets of permutations that avoid a single pattern. The study of these combinatorial objects was initiated by Donald Knuth in the 1960s when he investigated which permutations could be sorted by being passed through a stack.

Project Details

permutation class is a set of permutations closed downwards under the subpermutation (or containment) order. See [1] for a brief introduction or [5] for a full exposition. A principal class is one that can be defined as avoiding a single permutation: Av(τ) = { σ : σ avoids τ }. This project will explore fundamental questions concerning the structure of permutations in principal classes. In particular, two important monotonicity conjectures will be addressed:

Inversion Monotonicity Conjecture [4]: For all k and every non-increasing permutation τ, the number of τ-avoiding n-permutations with k inversions increases as increases.

Block Monotonicity Conjecture [3]: For all n and every skew-indecomposable permutation τ of length greater than 2, the number of τ-avoiding n-permutations with m skew blocks decreases as increases.

For both of these, the smallest case for which the conjecture is open is τ = 1324. Resolving the Inversion Monotonicity Conjecture for 1324-avoiders would yield an improved upper bound on the growth rate of the class. Understanding Av(1324) is one of the primary open problems in permutation classes research [2].

[1] David Bevan, Permutation patterns: basic definitions and notation, 2015.

[2] Bevan David, Robert Brignall, Andrew Elvey Price and Jay Pantone, A structural characterisation of Av(1324) and new bounds on its growth rate, European Journal of Combinatorics, 88:103115, 2020.

[3] Miklós Bóna, Supercritical sequences, and the nonrationality of most principal permutation classes, European Journal of Combinatorics, 83:103020, 2020.

[4] Anders Claesson, Vít Jelínek and Einar Steingrímsson, Upper bounds for the Stanley–Wilf limit of 1324 and other layered patterns, Journal of Combinatorial Theory, Series A, 119:1680–1691, 2012.

 [5] Vincent Vatter. Permutation classes. In Miklós Bóna, Handbook of enumerative combinatorics, 2015. Preprint version:


You should have (or expect to have) a UK Honours Degree (or equivalent) at 2.1 or above in Mathematics or a closely related subject with a high mathematical content.

The goal of this project is the exact enumeration of classes of permutations that can be plotted on monotone curves in grids. At present, an effective procedure is only known for so-called “skinny” classes. The general problem is challenging because permutations have multiple ways of being plotted on the curves.

Project Details

The monotone grid class Grid(M) consists of permutations that can be plotted on monotone curves in a grid. This grid is specified by the matrix M, all of whose entries are in {0, 1, –1}, where 1 and –1 denote monotone increasing and decreasing curves in a cell, and 0 denotes an empty cell. This project concerns the enumeration of these classes.

For a general overview of permutation classes, see Vatter’s recent survey [5]. An introduction to monotone grid classes can be found in [3, Chapter 2]. There is also an interactive demonstration, available from

Associated with a grid class is a graph whose structure influences its enumerative properties. If the graph is acyclic, then the class has a rational generating function [1]. If the graph is unicyclic, it is conjectured that the generating function is algebraic; otherwise, it is believed that the class is D-finite [3, Chapter 4]. The exponential growth rate of any monotone grid class can be determined from its matrix [2, 4], but an effective procedure for exact enumeration is only known for “skinny” grid classes, those defined by a k × 1 vector [3, Chapter 3]; these are acyclic. The general problem is hard because permutations typically have multiple “griddings” (different ways of being plotted on the curves).

The project is likely to focus on classes defined by a k × 2 matrix, seeking procedures for enumerating acyclic and unicyclic classes of this sort, and in the latter case proving algebraicity.

 [1] M. Albert, M.Atkinson, M. Bouvel, N. Ruškuc, V. Vatter. Geometric grid classes of permutations. Trans. Amer. Math. Soc., 2013.

 [2] M. Albert, V. Vatter. An elementary proof of Bevan’s theorem on the growth of grid classes of permutations. Proc. Edinburgh Math. Soc., 2019.

 [3] D. Bevan. On the growth of permutation classes. PhD thesis, 2015.

 [4] D. Bevan. Growth rates of permutation grid classes, tours on graphs, and the spectral radius. Trans. Amer. Math. Soc., 2015.

[5] V. Vatter. Permutation classes. In M. Bóna, Handbook of enumerative combinatorics, 2015. Preprint version:


You should have (or expect to have) a UK Honours Degree (or equivalent) at 2.1 or above in Mathematics or a closely related subject with a high mathematical content.

Supervisors: Bingzhang Chen, Michael Heath, Department of Mathematics and Statistics, University of Strathclyde

Michael Burrows, Scottish Association for Marine Science

Dafne Eerkes-Medrano, Rory O’Hara-Murray, Marine Scotland Science

Project Description

We are looking for a highly motivated, numerate student with an interest in marine plankton ecology and mathematical modelling to join our group. This fully funded 3.5-year studentship needs to be filled by 30 April 2021, so we recommend applying immediately.

Plankton are critically important for marine habitats supporting their food webs and influencing ecosystem health. They vary enormously in size – from the size of a bacterium to being visible to a naked eye. Size is one of the most important traits in plankton, determining their growth, respiration, resource uptake and vulnerability to predation. Plankton size also determines how much food is available to upper trophic levels such as fish. Therefore, it is crucial for us to understand what controls plankton size structure in the ocean. The environmental controls on plankton mean size have been extensively studied, but much less is known about what affects size diversity. The successful candidate will: 1) have the opportunity to tackle this problem by taking advantage of the long-term observational data in UK coastal waters; 2) build state-of-art plankton models and use the observational data to optimize these models; and 3) apply the plankton size-based models to answer questions regarding planktonic food-webs and trophic interactions in context of climate change.         


It is anticipated that you will receive substantial training in mathematical and statistical modelling including but not limited to analyses of ordinary and partial differential equations and Bayesian inference. You will also have the opportunity to use the high-performance computing system in Strathclyde ( Your mathematical, statistical, and programming skills are expected to be substantially enhanced during the PhD training. These skills will be very useful for securing some of the most popular jobs in this Big Data era. You will also gain a deep understanding of the ecology of biodiversity and coastal oceanography, which is essential for protecting our planet.

You will mainly work within the Marine Population Modelling group, Department of Mathematics and Statistics, University of Strathclyde ( You will also have the opportunity to collaborate with scientists in Scottish Association for Marine Science (SAMS) and Marine Scotland Science (MSS).


Applicants should have or expect to obtain a good honours degree (1, 2.1, or equivalent) in ecology, oceanography, applied mathematics, statistics, or a highly quantitative science. A highly quantitative background and experience of numerical modelling is desirable. Experience programming in R, Fortran, C/C++, Python, or Matlab would be highly beneficial, but not essential.

How to apply

To apply, send 1) a complete CV, 2) a 1 page personal statement explaining your interests and skills for this project, and 3) names and contact information of three references. In your personal statement please describe i) your interests and skills for this project, ii) your ability to critically analyze different sources of information and data, and iii) your motivation and desired training. Application materials are to be submitted to the lead supervisor, Dr Bingzhang Chen, Department of Mathematics and Statistics, University of Strathclyde, Glasgow at

We value diversity and welcome applications from all sections of the community.

The University currently holds a Bronze Athena SWAN award, recognising our commitment to advancing women’s careers in science, technology, engineering, maths and medicine (STEMM) employment in academia.

Key Information and Funding Notes

The project will start immediately, but with an official start date of 27th September 2021 and an induction event in Glasgow on 4th October 2021.

The student will be enrolled in the SUPER Graduate School and onto the SUPER Post Graduate Certificate in Researcher Professional Development.

The studentship is co-funded by the Scottish Universities Partnership for Environmental Research Doctoral Training Partnership (SUPER DTP; and University of Strathclyde. It is open to all nationalities. However, it is expected that non-UK students should bring their own funding to match up with the extra international fee. Funding for part-time study is an option, with a minimum of 50% of full-time effort being required.

Background reading

Acevedo-Trejos, E. et al. (2018). Proc. R. Soc. B, 285: 20180621.

Anderson, T.R., Gentleman, W.C. and Yool, A. (2015). Geosci. Mod. Dev., 8, 2231-2262.

Chen, B., Smith, S.L., & Wirtz, K. (2019). Ecol. Lett., 22, 56-66.

Haario, H., et al. (2006). Stat. Comp., 16, 339-354.

Schmidt, K., et al., (2020). Global Change Biol., 00:1-14.

Ward, B.A. et al. (2012). Limnol. Oceanogr., 57, 1877-1891.

Mathematics and statistics are at the heart of all scientific and engineering disciplines. Strathclyde has a strong international reputation in the use of mathematical modelling and analysis to solve many problems relevant to industry, business and wider society. The department's research interests are in Applied Analysis, Continuum Mechanics & Industrial Mathematics (CMIM), Numerical Analysis & Scientific Computing, Population Modelling & Epidemiology, and Stochastic Analysis.

A large number of faculty members in the CMIM group are interested in problems related to fluid mechanics. The study of droplet electrohydrodynamics is a classic fluid mechanical problem, pioneered by G. I. Taylor and has continued to intrigue scientists to the present day. The proposed research project will further the field of droplet EHD by studying the dynamics of a pair of interacting droplets in an electric field. Some articles relevant to the project can be found in the references below. The student will be jointly supervised by Dr Debasish Das and Prof Stephen Wilson. Visit the webpages below for more details.

Qualifications: A bachelors degree (upper second class honours or higher) in Mathematics or a related subject like Mechanical, Chemical Engineering or Physics is required. Applicant should have taken at least one undergraduate course on Fluid Mechanics (any advanced Fluid Mechanics course is highly desirable). Some experience in basic coding in any programming language is a plus.

Studentship details: The studentship covers home fees and stipend (UKRI minimum level - currently £15,609 for 21/22). All candidates are eligible, but international candidates would need to pay the fees difference between Home and Overseas rates. The duration of PhD is 36 months (extendable depending on availability of extra funds). Apply by March 14th, 2021 for full consideration.

Application: Visit the webpage below to apply and make sure to mention the title of the project and name of supervisors listed above.

1) D. Das and D. Saintillan, "Electrohydrodynamics of viscous drops in strong electric fields: Numerical simulations", Journal of Fluid Mechanics 829, 127-152 (2017).
2) D. Das and D. Saintillan, "A nonlinear small-deformation theory for transient droplet electrohydrodynamics", Journal of Fluid Mechanics 810, 225-253 (2017).
3) A. Bricard, J.-B. Caussin, D. Das, C. Savoie, V. Chikkadi, K. Shitara, O. Chepizhko, F. Peruani, D. Saintillan, D. Bartolo, "Emergent vortices in populations of colloidal rollers", Nature Communications 6, 7470 (2015).
4) L. T. Corson, C. Tsakonas, B. R. Duffy, N. J. Mottram, I. C. Sage, C. V. Brown, & S. K. Wilson, "Deformation of a nearly hemispherical conducting drop due to an electric field: Theory and experiment". Physics of Fluids, 26, 122106 (2014).
5) D. Das and D. Saintillan, "Electrohydrodynamic interaction of spherical particles under Quincke rotation", Physical Review E 87, 043014 (2013).

This project is situated at the interface between computational mathematics, engineering and machine learning and the student will benefit from the expertise of the supervisors in numerical methods, modelling and will have access to experimental data.

For many complex scientific and engineering problems there is usually a limited availability of experimental data and for this reason a new paradigm has emerged recently giving rise to a new scientific field, i.e. physics informed machine learning (PIML) consisting in a combination of the physical models, small data and machine learning tools. In this project we would like to apply these ideas to quenching in order to improve the overall mathematical and numerical models using available data, empirical laws but also existing models. This relies on the fact that current models are based primarily on experimental observations and existing models lack generality and are developed for specific conditions. 

This project is situated at the interface between computational mathematics, engineering and machine learning and the student will benefit from the expertise of the supervisors in numerical methods, modelling and will have access to experimental data.


Applicants should have, a first class or good 2.1 honours degree (or equivalent) in a relevant discipline. Highly motivated candidates from non-mathematical backgrounds are highly recommended to apply. To be eligible for a full award a student must have no restrictions on how long they can stay in the UK and have been ordinarily resident in the UK for at least 3 years prior to the start of the studentship.


Fully funded 4-year EPSRC PhD studentship in the Department of Mathematics and Statistics at the University of Strathclyde, Glasgow, United Kingdom, jointly supervised by Prof. Victorita Dolean and Dr. Salah Rahimi (AFRC). The studentship covers full tuition fees and a tax-free stipend for 4 years starting on the 1st of October with an attractive Research Training  Support Grant per annum.


Applications can be made here.

A fully funded three-year PhD studentship is available in the Department of Mathematics and Statistics at the University of Strathclyde, Glasgow, United Kingdom. The intra-disciplinary research will be supervised by Prof. Victorita Dolean and undertaken primarily within the Numerical Analysis and Scientific Computing group. Please see  for details of the group’s research. The student will also have the opportunity to interact with the Applied Analysis group, facilitated by the second supervisor, Dr. Matthias Langer; see

Mathematical and numerical modelling is unavoidable nowadays when one tries to investigate and understand complex physical phenomena such as seismic or electromagnetic wave propagation problems. When developing realistic mathematical models for large-scale physical applications, one bottleneck in the procedure is often the efficient and effective solution of the resulting matrix equations. In addition to the inherent difficulties one can encounter in complex applications, we often experience extra difficulties when dealing with time-harmonic wave propagation problems. These difficulties stem from the indefinite or non-self-adjoint nature of the operators involved. This requires a paradigm shift in the design and analysis of solvers. The aim of this project is to build and analyse a new generation of spectral preconditioners based on generalised eigenvalue problems allowing a robust behaviour with respect to the physical properties of the medium. This requires a combination of numerical analysis and spectral analysis tools. The outcome will be both mathematical but also practical, as this will fundamentally change the state of the art of solvers and the results will be incorporated in open-source software. 


Although the project will focus primarily on the time-harmonic Helmholtz equation, the techniques developed will be applicable to other equations of the same nature, arising in computational electromagnetism and seismology.

This is a very exciting project, which will allow the student to work at the interface between computational mathematics and analysis with a strong potential for application. The student will attend regular research seminars and events within the Mathematics and Statistics department, and so will have many opportunities to interact with a multi-disciplinary team and international collaborators and develop both technically and professionally.

Applicants should have, or be expecting to obtain in the near future, a first class or good 2.1 honours degree (or equivalent) in mathematics or a mathematical science.

Funding Notes:
The studentship covers full tuition fees and a tax-free stipend for three years starting on a commonly agreed date. Funding is only available to UK nationals and to EU nationals. For more information contact: and 

Classification of teas (types, quality grades, region of origin etc) has been examined by many researchers, using both chemical composition and more recently digital image analysis techniques to extract features from the image that are useful for classification.

Factors affecting the success of classification include the choice of features, the classifier and the imaging modality. Building on previous work at Strathclyde in collaboration with the EEE department, this project will allow the student to examine the choice of any of these to achieve optimal results. Intending students should have a strong statistical background and excellent computer skills, and be competent/be able to quickly become competent in the use of both R and Matlab.

Second supervisors: George Gettinby, Magnus Peterson

Worldwide losses of honey bee colonies have attracted considerable media attention in recent years and a huge amount of research. Researchers at Strathclyde have experience since 2006 of carrying out a series of surveys of beekeepers in Scotland ( and now have 5 years of data arising from these surveys. These data have been used to estimate colony loss rates in Scotland and to provide a picture of beekeepers’ experience and management practices.

This project will examine the data in more detail than has been done so far, and is likely to involve data modelling and multivariate methods to identify risk factors. Part of the project will involve establishing the spatial distribution of various bee diseases.

This project will build on links with the Scottish Beekeepers’ Association and membership of COLOSS, a network linking honey bee researchers in Europe and beyond. Intending students should have a strong statistical background and excellent computer skills, and be competent/be able to quickly become competent in the use of R.

In this project we shall look at how stochastic models can be used to describe how infectious diseases spread. We will start off by looking at one of the simplest epidemic models, the SIS (susceptible-infected-susceptible) model. In this model a typical individual starts off susceptible, at some stage catches the disease and after a short infectious period becomes susceptible again.

These models are used for diseases such as pneumococcus amongst children and sexually transmitted diseases such as gonorrhea amongst adults (Bailey, 1975). Previous work has already looked at introducing stochastic noise into this model via the disease transmission term (Gray et al. 2011). This is called environmental stochasticity which means introducing the random effects of the environment into how the disease spreads. This results in a stochastic differential equation (SDE) model which we have analysed. We have derived an expression for a key epidemiological parameter, the basic reproduction number.

In the deterministic model this is defined as the expected number of secondary cases caused by a single newly-infected individual entering the disease-free population at equilibrium. The basic reproduction number is different in the stochastic model than the deterministic one, but in both cases it determines whether the disease dies out or persists. In the stochastic SIS SDE model we have shown the existence of a stationary distribution and that the disease will persist if the basic reproduction number exceeds one and die out if it is less than one.

SDE Models with Environmental Stochasticity
We have also looked at other SDE models for environmental stochasticity. One of these took a simple deterministic model for the effect of condom use on the spread of HIV amongst a homosexual population and introduced environmental stochasticity into the disease transmission term. Again we found that a key parameter was the basic reproduction number which determined the behaviour of the system.

As before this was different in the deterministic model than the stochastic one. Indeed it was possible for stochastic noise to stabilise the system and cause an epidemic which would have taken off in the deterministic model to die out in the stochastic model (Dalal et al., 2007). Similar effects were observed in a model for the internal viral dynamics of HIV within an HIV-infected individual (Dalal et al., 2008).

Demographic Stochasticity
The real world is stochastic, not deterministic, and it is difficult to predict with certainty what will happen. Another way to introduce stochasticity into epidemic models is demographic stochasticity. If we take the simple homogeneously mixing SIS epidemic model with births and deaths in the population we can derive a stochastic model to describe this situation by defining p(i, j, t) to be the probability that at time t there are exactly i susceptible and j infected individuals and deriving the differential equations satisfied by these probabilities.

Then we shall look at how stochastic differential equations can be used to approximate the above set of equations for p(i, j, t). This is called demographic stochasticity and arises from the fact that we are trying to approximate a deterministic process by a stochastic one (Allen, 2007). Although the reasons for demographic and environmental stochasticity are quite different the SDEs which describe the progress of the disease are similar. The first project which we shall look at is analysis of the SIS epidemic model with demographic stochasticity along the lines of our analysis of the SIS epidemic model with environmental stochasticity.

Further Work
After this we intend to look at other classical epidemiological models, in particular the SIR (susceptible-infected-removed) model in which an individual starts off susceptible, at some stage he or she catches the disease and after a short infectious period he or she becomes permanently immune. These models are used for common childhood diseases such as measles, mumps and rubella (Anderson and May, 1991). We would look at introducing both environmental and demographic stochasticity into this model.

Other epidemiological models which could be analysed include the SIRS (susceptible-infected-removed-susceptible) epidemic model, which is similar to the SIR epidemic model, except that immunity is not permanent, the SEIS (susceptible-exposed-infected-susceptible) model which is similar to the SIS model, but includes an exposed or latent class, and the SEIR (susceptible-exposedinfected- removed) model, which similarly extends the SIR model.

We would also aim to look at other population dynamic models such as the Lotka-Volterra predator-prey model. There is also the possibility of developing methods for parameter estimation in all of these epidemiological and population dynamic models, and we have started work on this with another Ph. D. student (J. Pan).

1. E. Allen, Modelling with Itˆo Stochastic Differential Equations, Springer-Verlag, 2007.
2. R.M. Anderson and R.M. May, Infectious Diseases of Humans: Dynamics and Control, Oxford University Press, Oxford, 1991.
3. N.T.J. Bailey, The Mathematical Theory of Infectious Disease and its Applications, Second Edition, Griffin, 1975.
4. A.J. Gray, D. Greenhalgh, L. Hu, X.
5. N. Dalal, D. Greenhalgh and X. Mao, A stochastic model for AIDS and condom-use. J. Math. Anal. Appl. 325, 36-53, 2007.
6. N. Dalal, D. Greenhalgh and X. Mao, A stochastic model for internal HIV dynamics. J. Math. Anal. Appl. 341, 1084-1101, 2008.

Differential equation models are commonly used to model infectious diseases. The population is divided up into compartments and the flow of individuals through the various classes such as susceptible, infected and removed is modelled using a set of ordinary differential equations (Anderson and May, 1991, Bailey, 1975). A basic epidemiological parameter is the basic reproduction number. This is defined as the expected number of secondary cases produced by a single newly infected case entering a disease-free population at equilibrium (Diekman and Heesterbeek). Typically the disease takes off if R0 > 1 and dies out if R0≤1.

However media awareness campaigns are often used to influence behaviour and if successful can alter the behaviour of the population. This is an area which has not been studied much until recently. The student would survey the existing literature on media awareness models in the literature and with the supervisor formulate mathematical models using differential equations for the effect of behavioural change on disease incidence. These would be examined using both analytical methods and computer simulation with parameters drawn from real data where appropriate. The mathematical techniques used would be differential equations, equilibrium and stability analyses and computer simulation.

1. R.M. Anderson and R.M. May, Infectious Diseases of Humans: Dynamics and Control, Oxford University Press, Oxford, 1991.
2. N.T.J. Bailey, The Mathematical Theory of Infectious Disease and its Applications, Second Edition, Griffin, 1975.
3. O. Diekmann, J. A. P. Heesterbeek and J. A. J. Metz, On the definition and computation of the basic reproduction number R0 for infectious diseases in heterogeneous populations. J. Math. Biol. 28, 365-382.
4. A. K. Misra, A. Sharma and J. B. Shukla, Modelling and analysis of effects of awareness programs by media on the spread of infectious diseases. Math. Comp. Modelling 53, 1221- 1228.
5. A. K. Misra, A. Sharma, V. Singh, Effect of awareness programs in controlling the prevalence of an epidemic with time delay, J. Biol. Systems, 19(2), 389-402,

Summary of PhD project:  The project deals with VISIBILITY GRAPHS. It will involve numerical work (kinetic Monte Carlo simulations) as well as methods of network and graph theory, primarily spectral analysis of adjacency matrices and Laplacians of the visibility graphs, and centrality and communicability indices of these graphs, Voronoi cell decompositions, and at a later stage Minkowski functionals and persistent homology. Thus this is a project that applies a variety of analytical, topological, and computational tools to an important industrial problem which we will describe below.

Visibility graphs will be used to allow us better to differentiate between mechanisms of realistic multidimensional extended island Submonolayer Deposition (SD) processes as the first step to a better control of the resulting morphology. For different processes, different morphologies of the resulting surface (substrate covered in islands) are important. For quantum dots, for example, one would like to have islands of particular size and shape periodically spaced on the surface; in other contexts uniform layers of deposition are needed as basis for "sandwich''-like arrangements of materials. The overall aim is to extend the machinery created by Allen, Grinfeld and Mulheran Physica A 532 (2019), 121872) for SD in a one-dimensional setting and point islands to a realistic multidimensional context involving extended islands.

Supervisors: M. Grinfeld (Mathematics and Statistics) and P. A. Mulheran (Chemical and Process Enginnering)

Funding: The project is fully funded by the Engineering and Physical Sciences Research Council (EPSRC) for 48 months. The successful recipient of the award will have their full Home/EU fees covered for the 4-year duration of the project, as well as receiving an annual stipend for living costs. The stipend rate for the 2020/21 academic year is £15,285 per annum. 

Additionally, the award provides a Research Training Support Grant (RTSG) of £5,000 over the 4-year duration of the studentship for the purpose of incidental costs associated with conference attendance, travel for research purposes and consumables.

In recent years there has been much work on reaction-diffusion equations in which the diffusion mechanism is not the usual Fickian one. Examples are integro-differential equations, porous media type equations, pseudodifferential equations, p-Laplacian type equations and prescribed curvature type (saturating flux) equations.

The motivation for this work comes from material science and mathematical ecology. However, there are applied contexts where these diffusion mechanisms have never been considered. One is in the area of combustion and the other is in the area of regularised conservation laws and shock propagation. This project, which would build on the work I did through the years on integrodifferential models and recently with M. Burns on the prescribed curvature equations, will use PDE, asymptotic, and topological methods to explore the dynamics of blowup and of shock propagation in canonical examples of reaction equations and nonlinear scalar conservation laws regularised by non-Fickian diffusion terms.


[1] M. Burns and M. Grinfeld, Steady state solutions of a bistable quasilinear equation with saturating flux, European J. Appl. Math. 22 (2011), 317-331.

[2] M. Burns and M. Grinfeld, Steady state solutions of a bistable quasilinear equation with saturating flux, European J. Appl. Math. 22 (2011), 317-331.

Recently, a new class of model has been developed to describe, for example, phase separation in materials such as binary alloys. These take the form of integrodifferential equations. Coarsening, that is, creation of large scale patterns in such models is poorly understood.

There are partial results [1, 2] that use the maximum principle, while for most interesting problems such a tool is not available. This will be a mixture of analytic and numerical work and will need tools of functional analysis and semigroup theory.


[1] D. B. Duncan, M. Grinfeld, and I. Stoleriu, Coarsening in an integro-differential model of phase transitions, Euro. J. Appl. Math. 11 (2000), 561-572.

[2]  V. Hutson and M. Grinfeld, Non-local dispersal and bistability, Euro. J. Appl. Math. 17 (2006), 221-232.

The dispersal of plant diseases is among the most important side effects of a closely integrated global economy. There are many examples of plant diseases that were introduced to the UK and other countries by trade, including Phytophthora ramorum, Dutch elm disease and ash dieback. The number of new plant diseases appearing in Europe each year more than quadrupled during the 20th and the early 21st century.

The plant trading network of the UK is likely to undergo significant modifications due to policy changes, both Brexit-related and due to potential reorientation of the British agriculture towards more emphasis on conserving the environment. This might result in an increase in long-range trade with more diverse partners, resulting potentially in the rise of the risk of importing pests, or an increase in domestic production where non-compliant businesses create larger risks. Thus, introducing stricter regulation might have an unintended consequence of a rearrangement of trading networks which may lead to a shift in the risk pathways rather than the overall reduction. The diversification and increased short-term dynamics of the trading networks is also associated with the rise of e-commerce. The rise of internet trading affects both the traditional supplier (e.g. plant nurseries) and the individual customer, resulting in a potential loss of traceability and quality.

By combining data analysis with bioeconomic modelling, this project aims to develop a framework to analyse the risks associated with plant trade, to highlight the pathways associated with high risk, and to assess strategies that can be used to minimise the risks at different border points (international and domestic “borders”). Firstly, the research will look to assess the gains from combining different data sources as well as improved data. This might include studying public data such as that held for England & Wales at FERA, as well as a consideration of statutory plant movement data that is currently privately held and unlinked. Secondly, we will use the novel bioeconomic framework to study influence of changes in disease risk on the change of trade decisions on the way buyers and sellers are connected. Finally, we will use the cutting-edge mathematical models of dynamic and adaptive networks to capture the traders behaviour whereby the individuals alter the pattern of with whom to trade and how much to trade in response to the epidemic.

The studentship is jointly funded by Defra and the University of Strathclyde for a 3.5 years study period. Applicants should have a first-class or a 2.1 honours degree in a relevant subject; Masters degree will be an advantage. A more detailed plan of the studentship is available to candidates upon application. Funding is available for UK and European applications.

Community detection is an essential tool in the analysis of complex networks with diverse applications such as identifying genes related to cancer, uncovering terror cells on Twitter, and understanding links between politicians. In the case of undirected networks, a simple and widely accepted definition of a community has led to an abundant body of research and many effective algorithms but when the network is directed the field is much more sparsely populated due to the lack of consensus surrounding the properties a directed community should possess. This project will build on a recent framework based on higher-order representations of network which has had some success and will build on existing work by the supervisors to produce methods tailored to the needs of the intelligence community. The main focus will be on unifying the problem of community detection in directed networks. The project will blend cutting edge tools for mathematical analysis with algorithm development and extensive investigation of applications.


Applicants should have, a first class or good 2.1 honours degree (or equivalent) in a relevant discipline. Highly motivated candidates from non-mathematical backgrounds are highly recommended to apply. To be eligible for a full award a student must have no restrictions on how long they can stay in the UK and have been ordinarily resident in the UK for at least 3 years prior to the start of the studentship.


Fully funded 4-year EPSRC PhD studentship in the Department of Mathematics and Statistics at the University of Strathclyde, Glasgow, United Kingdom, jointly supervised by Dr Philip Knight and Dr Luce le Gorrec. The studentship covers full tuition fees and a tax-free stipend for 4 years starting on the 1st of October with an attractive Research Training  Support Grant per annum.


Applications can be made here.

Up to 2002, most of the existing strong convergence theory for numerical methods requires the coefficients of the SDEs to be globally Lipschitz continuous [1]. However, most SDE models in real life do not obey the global Lipschitz condition. It was in this spirit that Higham, Mao and Stuart in 2002 published a very influential paper [2] (Google citation 319) which opened a new chapter in the study of numerical solutions of SDEs---to study the strong convergence question for numerical approximations under the local Lipschitz condition.

Since the classical explicit Euler-Maruyama (EM) method has its simple algebraic structure, cheap computational cost and acceptable convergence rate under the global Lipschitz condition, it has been attracting lots of attention.

Although it was showed that the strong divergence in finite time of the EM method for SDEs under the local Lipschitz condition, some modified EM methods have recently been developed these SDEs. For example, the tamed EM method was developed in 2012 to approximate SDEs with one-sided Lipschitz drift coefficient and the linear growth diffusion coefficient. The stopped EM method was developed in 2013. Recently, Mao [3] initiated a significantly new method, called the truncated EM method, for the nonlinear SDEs. The aim of this PhD is to develop the truncated EM method. The detailed objectives are:

(1) To study the strong convergence of the truncated EM method in finite-time for SDEs under the generalised Khasminskii condition and its convergence rate.

(2) To use the truncated EM method to investigate the stability of the nonlinear SDEs. Namely to study if the numerical method is stochastically stable when the underlying SDE is stochastically stable and to study if we can infer that the underlying SDE is stochastically stable when the numerical method is stochastically stable for small stepsize.

A PhD studentship might be available for the project.


[1] Mao X., Stochastic Differential Equations and Applications, 2nd Edtion, Elsevier, 2007.

[2] Higham D., Mao X., Stuart A., Strong convergence of Euler-type methods for nonlinear stochastic differential equations, SIAM J. Numer. Anal. 40(3) (2003), 1041--1063.

[3] Mao X., The truncated Euler-Maruyama method for stochastic differential equations, J. Comput. Appl. Math. 290 (2015), 370--384.

Income needs seem to be a top priority at the moment and with low savings rates and top UK equity income funds yielding less than 4\%, it is perhaps easy to understand why. With savings rates continuing at their record lows, some savers are turning to alternatives. It is in this spirit that many financial institutions are offering stock market linked savings plans to those looking to combine a high yield opportunity with some protection against a falling stock market. That is why the stock market linked savings accounts have recently become very popular. The returns of these accounts are random so the returns, even the initial capital, are not guaranteed. They are very much different from the familiar fixed-term-fixed-rate savings accounts.

The aim of this PhD project is to perform the stochastic and numerical analysis on the stock market linked savings accounts in order to establish the theory on the mean percentage of return (MPR). The MPR depends mainly on two factors:

(1) The structure of the saving accounts, namely the terms of the portfolios (plans);

(2) The behaviour of the stock market linked.

There are various portfolios in the market. This PhD project will analyze a number of typical plans. On the stochastic modelling of the stock market, there are various stochastic differential equation (SDE) models. In this project, some of these SDE models will be used. The key objective here is to establish the explicit formulas for the MPRs of the underlying stock marker linked saving accounts if possible; otherwise develop some new techniques to establish better approximation schemes.

The project will then develop the techniques of the stochastic and numerical analysis to deal with other more complicated financial derivatives including bond, fund.

A PhD studentship might be available for the project.

Cholesteric liquid crystals are chiral systems which possess a spontaneously formed helical structure with the pitch in micron range which is important for various applications in optics and nanophotonics. In recent years the interest has shifted in the direction of lyotropic cholesterics which are the solutions of various chiral macromolecules, viruses or chiral nanocrystals. These systems are important for biology (for example, cholesteric states of DNA) and also provide some very useful natural anisotropic chiral materials.

Among the most interesting resources to explore are cellulose and chitin, key biopolymers in the plant and animal world, respectively. Both have excellent mechanical properties and  can be extracted as nanorods with high degree of crystallinity.Both are also chiral. Molecular chirality of such nanorods is amplified into a helically modulated long-range ordered cholesteric liquid crystal phase when they are suspended in water.

The aim of this project is to develop a molecular-statistical theory of chirality transfer in cholecteric nanorod phase, determined by steric and electrostatic chiral interactions, and quantitatively describe the variation of helix pitch as a function of rod length, concentration, dispersity and temperature. The theory will be built upon the previous results, obtained for different cholesteric liquid crystals ((see some references to our work below).

The project will include a collaboration with two experimental group at the University of Luxembourg and the University of Stuttgart.  These groups have an enormous expertise in the field of lyotropic liquid crystals.

[1] Honorato-Rios, C., Lehr, C., Sch¨utz, C., Sanctuary, R., Osipov, M. A., Baller, J. and Lagerwall, J. P.F.., Fractionation of cellulose nanocrystals: enhancing liquid crystal ordering with- out promoting gelation, Asia Materials, 10, 455–465 (2018).

[2]. Dawin, Ute C., Osipov, Mikhail A. and Giesselmann, F. Electrolyte effects on the chiral induction and on its temperature dependence in a chiral nematic lyotropic liquid crystal J of Phys. Chem. B, 114 (32). 10327-10336 (2010)

[3] A. V. Emelyanenko, M. A. Osipov and D. A. Dunmur, ]  Molecular theory of helical sense inversions in chiral nematic liquid crystals Phys. Rev. E, 62, 2340 (2000)


Elastic constants of nematic liquid crystals, which describe the energy associated with orientational deformation of such anisotropic fluids, are among the most important parameters for various applications of liquid crystal materials. The elastic constants of nematic liquid crystals have been well investigated both experimentally and theoretically in the past. During the past decade a number of novel liquid crystals materials with unconventional molecular structure have been investigated and it has been found that these systems are characterised by the anomalous values and behaviour of the elastic constants. In particular, it has been shown that in the nematic phase exhibited by the so-called V-shaped bent-core liquid crystals two of the three elastic constants decrease nearly to zero with the decreasing temperature. This behaviour is still very poorly understood.

It should be noted that bent-core liquid crystals attract a very significant attention at present because they also exhibit a number of unusual novel phases with a nanoscale helical structure. It is now generally accepted that a transition into these unusual phases may be driven by the dramatic reduction of the elastic constants.

The aim of this project is the generalise the existing molecular-statistical theory of elasticity of nematic liquid crystals to the case of bent-core nematics, composed of biaxial and polar molecules, using the preliminary results obtained in recent years (see, for example, the references to some of our recent papers given below). Another aim is to explain the existing experimental data on the temperature variation of the elastic constants of bent-core nematic liquid crystals.

The project will include a collaboration with the experimental group at the University of Leeds and the theoretical group from Russian Academy of Sciences.  These collaborations are very important for  the success of the project.

[1] M. A. Osipov and G. Pajak, Effect of polar intermolecular interactions on the elastic constants of bent-core nematics and the origin of the twist-bend phase, The European Physical Journal E 39, 45 (2016).

[2] M. A. Osipov and G. Pajak, Polar interactions between bent-core molecules as a stabilising factor for inhomogeneous nematic phases with spontaneous bend deformations, Liquid Crystals 44, 58 (2016).

[3] S. Srigengan, M. Nagaraj, A. Ferrarini, R. Mandle, S.J. Cowling, M.A. Osipov, G. Pająk, J.W. Goodby and H.F. Gleeson, J. Mater. Chem. C, 2013, 6, 980

We wish to develop innovative methods for modelling high-dimensional time series. Practical time series data, including both continuous-valued and discrete-valued data such as climate record data, medical data, and financial and economic data, are used for empirical analysis.

Models for forecasting multivariate conditional mean and multivariate conditional variance (volatility) are concerned. Techniques for dimension reduction, such as dynamic factor analysis, are used.

The estimation of models for panel data analysis and the option valuation with co-integrated asset prices is discussed.

Nowadays people often meet problems in forecasting a functional. A functional may be a curve, a spatial process, or a graph/image. In contrast to conventional time series analysis, in which observations are scalars or vectors, we observe a functional at each time point; for example, daily mean-variance efficient frontiers of portfolios, yield curves, annual production charts and annual weather record charts.

Our goal is to develop new models, methodology and associated theory under a general framework of Functional Time Series Analysis for modelling complex dynamic phenomena. We intend to build functional time series models and to do forecasting.

When the true economic system consists of many equations, or our economic observations have a very high dimension, one may meet the ``curse of dimensionality" problem. We try to impose a common factor structure to reduce dimension for the parametric and nonparametric stability analysis of a large system. Replacing unobservable common factors by principle components in parametric and nonparametric estimation will be justified.

In contrast to conventional factor models which focuses on reducing dimensions and modeling conditional first moment, the proposed project devotes attention to dimensional reduction and statistical inference for conditional second moments (covariance matrices). The direct motivation lies in the increasing need to model and explain risk and uncertainty of a large economic system.

The other distinctive point is that the proposed project considers factor models for high frequency data. A key application is the analysis of high dimensional and high-frequency financial time series, although the potential uses are much wider.

Marine ecosystems are generally composed of large numbers of species of widely varying sizes, ranging from unicellular species, through zooplankton and up to large fish and whales. The distribution of the total biomass of all species by size is known as the biomass spectrum.

In addition to the size variation due to differing characteristic sizes of the different species, and unlike the case in terrestrial systems, individuals themselves often undergo increases in body size of several orders of magnitude, from small eggs and larvae at a few millimetres in length up to large adults at the metre length scale.

At different parts of its life cycle an individual will be present at different parts of the biomass spectrum. Despite this apparent complexity it has long been known from field observations that biomass spectra show many regularities. In particular the logarithm of biomass density is approximately linearly related to the logarithm of body length with negative slope. Moreover, the slope of the spectrum is potentially sensitive to environmental and anthropogenic perturbations, for example the removal of large fish due to commercial fishing.

For these reasons biomass spectra have gained currency in recent years as a tool for studying the integrated ecosystem impacts of climate change and human exploitation of the seas.

The relative simplicity of representing the entire ecosystem as a size-structured spectrum has also permitted the development of mathematical representations in terms of partial differential equations, and these can be used to make predictions about ecosystem level responses to fishing and environmental change.

To date most modelling efforts have focused on steady state analyses of biomass spectra, which may be compared to annually averaged size spectra from field observations. In temperate shelf seas such as the North Sea, however, the biomass spectrum is not static but subject to seasonal impulses caused by increased primary production from phytoplankton in the spring bloom, and by seasonal reproduction by zooplankton and fish. This is known from both observational and mathematical models to induce annual ripples in the biomass distribution that propagate up the spectrum, gradually attenuating at larger sizes.

Fish larvae can exploit this by growing in size at a rate that allows them to feed near the peak of the wave, a phenomenon that has been dubbed by John Pope and his co-workers “surf-riding the biomass spectrum”. This project will focus on developing existing models to better represent these processes. In order to test the models the parameters will be estimated using Bayesian inference methods by fitting to a variety of data sets, including a long term (multi-annual) high temporal resolution (weekly) data from the North Sea.

Many fish populations worldwide have been heavily exploited and there is accumulating evidence from both observational and theoretical studies that this harvesting can induce evolutionary changes. Such responses can affect the stock sustainability and catch quality, and so there is a recognized need for new management strategies that minimise these risks. Most results suggest that high mortality on larger fish favours early maturation.

However, recent theoretical work has shown that trade-offs between growth and maturation can lead to more complex evolutionary responses. Surprisingly, harvesting large fish can select for either late or early maturation depending on the effect of maturation on growth rate. To date most theoretical studies have used evolutionary invasion analyses on simple age-based discrete-time models or on continuous-time coupled ODE representations of size structure.

In common with many generic models of fish population dynamics, population control occurs by unspecified density-dependence at settlement. While these simplifications carry the advantage of analytical tractability, the analysis assumes steady state populations. This, together with the stylised life-histories precludes comparing model results with field data on secular changes in size-distributions an sexual maturity.

The work in this project will develop a new generation of testable model for fisheries-induced adaptive changes with the potential to inform future management decisions. This will involve developing a consumer-resource model which a length-structured fish population feeding on a dynamic biomass spectrum.

Differently-sized fish will compete for food by exploiting overlapping parts of the food size spectrum. The population will be partitioned by length at maturity, and this will be the heritable trait under selection. The model will be used to explore how changes in mortality and food abundance affect the evolutionarily stable distribution of maturation lengths.

Comparisons with survey data on North Sea demersal fish will be used to assess whether the historical harvest rates are sufficient to explain growth rate changes as an evolutionary response. Finally the evolutionarily stable optimal harvesting strategies will be identified.

The evaporation of sessile droplets is an area of very active multidisciplinary research, with new publications appearing on an almost daily basis and entire international conferences now dedicated to the topic. Sessile droplets appear in numerous contexts is nature, biology, industry and medicine, and are currently the subject of a major international research effort on mathematics, physics, chemistry and engineering. The aim of the present project is to use a range of applied mathematical techniques to tackle two exciting new aspects of this scientifically and practically important problem, namely the enhanced interaction between confined droplets and the evaporation of droplets on porous surfaces. This project builds on the supervisors’ extensive track records of research on various aspects of droplet evaporation, and is in collaboration with a programme of cutting-edge experimental work to be conducted at Edinburgh University. The student will join a lively and mutually supportive cohort of fellow students and postdocs within the Continuum Mechanics and Industrial Mathematics (CMIM) research group led by Professor Wilson.

A fully funded 4-year EPSRC PhD studentship is available in the Department of Mathematics and Statistics at the University of Strathclyde, Glasgow, United Kingdom. The multidisciplinary research will be supervised by Professor Stephen K. Wilson and Dr Alexander W. Wray from the Continuum Mechanics and Industrial Mathematical (CMIM) research group at the University of Strathclyde (where the project will be based) and Professor Khellil Sefiane from the School of Engineering at the University of Edinburgh.

Applicants should have, a first class or good 2.1 honours degree (or equivalent) in a relevant discipline (i.e mathematics, physics or engineering-related disciplines with a background in applied mathematics and/or fluid mechanics).

The studentship covers full tuition fees and a tax-free stipend for 4 years starting on the 1st of October with an attractive Research Training  Support Grant per annum. To be eligible for a full award a student must have no restrictions on how long they can stay in the UK and have been ordinarily resident in the UK for at least 3 years prior to the start of the studentship. Deadline for application: 3rd September 2021

Interested candidates are strongly encouraged to contact the supervisors for informal discussions about the project via and as soon as possible.


The behaviour of sessile droplets is an area of very active international research, with new publications appearing on an almost daily basis and entire conferences now dedicated to the topic. Over the last decade, Professor Stephen Wilson has collaborated very successfully with Professor Khellil Sefiane from the School of Engineering at the University of Edinburgh (and a Visiting Professor at the University of Strathclyde) of a variety of practically important fluid-dynamical problems, including evaporating droplets, bubble dynamics, self-rewetting fluids, and anti-surfactants.

The aim of the present project is to build on the proposed supervisors’ previous work on evaporating sessile droplets to explore two exciting new aspects of this scientifically and practically important problem.

Very recent work by Sefiane and his collaborators have provided the first comprehensive experimental investigation of vapour absorption by sessile droplets of a desiccant liquid (i.e. one which draws moisture from the air). The mathematical modelling and analysis of such systems is an exciting and challenging open problem.

In practice, droplets almost never occur singly, but, due to the inherent complexity of the multiple-droplet problem, so far very little work has been done on the interactions between evaporating droplets. The aim of the proposed work is to investigate the fascinating but virtually unexplored subject of the collective behaviour of large arrays of small sessile droplets. Interactions between the droplets (in particular, so-called “shielding” effects) are expected to lead to very different collective behaviour compared to that of isolated droplets.

The student will join a lively and mutually supportive cohort of fellow PhD students within the Continuum Mechanics and Industrial Mathematics (CMIM) research group.

You should have (or expect to have) a UK Honours Degree (or equivalent) at 2.1 or above in Mathematics, Mathematics and Physics, Physics or a closely related discipline with a high mathematical content. Knowledge of Continuum Mechanics and mathematical methods (such as asymptotic methods) for the solution of partial differential equations is desirable (but not essential, particularly for overseas applicants).

Informal enquiries can be made to the lead supervisor, Professor Stephen K. Wilson, Department of Mathematics and Statistics, University of Strathclyde, Glasgow at and/or +44(0)141 548 3820. However, formal applications must be made via the online application procedure which can be found at

remembering to list the title of the project as “Mathematical Modelling and Analysis of Sessile Droplets” and Professor Stephen K. Wilson as the first supervisor. There is no need to include a detailed research plan, but a brief outline of your relevant experience (if any) and your motivation for choosing this project would assist with the selection procedure.

In recent years there has been an explosive growth of interest in the behaviour and control of fluids at small (typically sub-millimetre) scales motivated by a range of novel applications including ink-jet printing and lab-on-a-chip technologies.

Much of the most exciting current research concerns the interaction between fluids and both rigid and flexible structures at small scales, and so the aim of the present project is to use a judicious combination of asymptotic methods and judiciously chosen numerical calculations to bring new insight into the behaviour of a variety of novel fluid-structure interaction problems in microfluidics.

In the last decade or so there has been an explosion of interest in droplet evaporation, driven by new technological applications as diverse as crop spraying, printing, cooling technologies such as heat pipes, and DNA micro-array analysis.

One particularly interesting aspect of this problem which has thus far received relatively little attention is that of fluids whose surface tension exhibits a local minimum with temperature, known as self-rewetting fluids, a property that can have a profound effect on the dynamics of droplets on heated substrates.

The aim of the project is to build on the existing literature on conventional surface-tension-gradient driven spreading and droplet drying (see, for example, the references to some of our recent work on these problems given below) to bring new physical insight into this challenging scientific problem, and hence to harness the novel properties of self-rewetting droplets in a range of applications.

The project will be a collaboration colleagues at the University of Edinburgh who will be undertaking a parallel series of experimental investigations on this problem which will be key to the successful outcome of the project.

Dunn, G.J., Wilson, S.K., Duffy, B.R., David, S., Sefiane, K. “The strong influence of substrate conductivity on droplet evaporation” J. Fluid Mech. 623 329-351 (2009)

Dunn, G.J., Duffy, B.R., Wilson, S.K., Holland, D. “Quasi-steady spreading of a thin ridge of fluid with temperature-dependent surface tension on a heated or cooled substrate” Q. Jl. Mech. appl. Math. 62 (4) 365-402 (2009)