Postgraduate research & PhD opportunities

With this project, we propose an investigation into a variety of dynamics and effects produced by the interaction of a droplet or a group of droplets with a solid or liquid surface. Related technological applications abound in the fields of thermal, mechanical and chemical engineering.

With this project, we propose an investigation into a variety of dynamics and effects produced by the interaction of an array of buildings (or a set of heat sources in an industrial plant or in a power plant) with a cross flow (horizontal wind).

With this project, we propose an investigation into a variety of flow configurations driven by gravity (buoyancy convection) at very high temperatures and/or driving temperature gradients

With this project, we propose a numerical investigation into a variety of dynamics and effects produced by the interaction of an advancing solidification front with thermally-driven convection in the melt.

We propose an investigation into a variety of dynamics and effects produced by the interaction of particles with fluid flow driven by a temperature gradient. Related technological applications abound in the fields of thermal, mechanical, nuclear and chemical engineering (at several scales).

The relevance of self-organization, pattern formation and non-equilibrium behaviour in a wide range of problems, related to macromolecular crystal engineering and typical pharmaceutical processes for the production of drugs and medicines, calls for a concerted approach using the tools of statistical physics

Aim of the present project is the modelling and numerical simulation of soft-tissue growth in rotating bioreactors and related morphological evolution. Numerical simulations will be used as a relevant and suitable tool in the analysis of such dynamics.

A three-year PhD project offered by the High Voltage Technologies (HVT) Research Group based within the Institute of Energy & Environment.

A three year PhD project offered by the High Voltage Technologies (HVT) Research Group, focused on the development of advanced impulsive non-thermal plasma systems for air cleaning and aerosol decontamination operations.

A three year PhD investigating the efficiency of transient non-thermal plasma discharges for different environmental applications is offered by the High Voltage Technologies (HVT) Research group within the Institute for Energy & Environment.

A 36-month full-time, fully funded Strathclyde/NPL/Synaptec PhD Studentship with the aim to investigate a range of electrical, mechanical, photonic and materials science aspects of hybrid fibre-optic voltage and current sensors in order to drive the limits of their measurement performance in smart grid applications.

Two 36 month PhD studentships fully funded by the US Air Force Office for Scientific Research (US AFOSR) are available focussing on fundamental and algorithmic research into novel Neuromorphic Spiking Neural Networks models for processing event data streams from multiple UAVs.

This PhD will explore how bacterially generated materials can be modified by incorporation of polymers and nanoparticles to enhance their mechanical properties. In this way, bacterially generated materials could be modified for specific tasks, such as earthquake and weather resistance.

Bio-deterioration of concrete strongly affects much of our built heritage and is particularly notable in wet territories like the UK or South East Asia. How to effectively solve bio-deterioration of concrete sculptures and buildings is an environmental, societal and scientific challenge.

The project focuses on laboratory and field investigation of the effects of root architecture on evapotranspiration processes and hydraulic conductivity of the rhizosphere. This is aimed at designing remedial measures to prevent diffuse shallow landsliding.

This PhD will practically explore how robotically applied sensors, repairs and smart materials can be used to enhance the integrity and safety of civil infrastructure.

This PhD project will assess the effects of air pollutant exposure on the efficacy of medical treatments for respiratory and cardiovascular conditions, in collaboration with and the NHS in Scotland and Ricardo Energy & Environment.

There is growing research interest in exploiting biologically-mediated mineral precipitation to develop new methods for nuclear waste treatment. This PhD project will investigate using bacterial apatites to remove radionuclides, such as 3H and 36Cl from gaseous and aqueous waste streams.

The aim of this project is to develop a practical approach to estimate the economic value of data used within engineering seismology, i.e. the assessment of the earthquake loading that a structure or infrastructure may be subjected to during its lifetime.

This project will develop models to assess human performance after the occurrence of a disruptive event of interconnected critical infrastructures.

The research will investigate the prevalence, transport and impact of microplastic pollution in our urban environments. The aim of this work in to provide a detailed quantitative understanding of key sources, pathways and transport through to deposition and sinks of atmospheric microplastic.

The research scope of “Multi-Agent Planning” has at its centre the study and development of multi-agent task and path planner that also identifies the appropriate type of perception, mapping and localisation methods for varying tasks, application context and dynamic environment condition.

This studentship will explore the conditions needed to succeed in the translation of sustainable manufacturing R & D into real CO2 reductions implemented in industrial supply chains.

This studentship will explore the question of whether sustainable supply chains are feasible for a range of engineering products.

The aim of this studentship is to investigate new business models likely to disrupt manufacturing.

Filtration and washing of pharmaceutical products is classically undertaken empirically. This project will use nano-computed tomography (nano-CT), a high-resolution cross-sectional imaging technique to track the progress of washing at high resolution in real time.

This modelling and simulation study will investigate the complex processes that occur when foam, rather than water, is used as a carrier for fibres during papermaking, with a view towards reducing the overall water footprint of the paper production process.

This project aims to develop a new computational tool, combining molecular simulations and machine learning approaches, to predict the solubility of complex pharmaceutical molecules in a variety of solvents.

Focussed on the development of novel sorption systems for water remediation, the project combines materials development, characterisation and testing for a range of pollutants, including pharmaceuticals and heavy metal species.

Focussed on understanding the impact of teaching strategies within a chemical engineering programme to both evaluate current acquisition of industry-ready graduate attributes with a view to informing educational changes required to best support student development.

This project is to develop and assess modelling methods to obtain a deeper insight into the physico-chemical processes of biomass conversion.

This project will undertake studies on the processes and technology required to convert biomass waste into a range of hydrocarbons. This research project requires both modelling and experimental studies to analyse the waste to energy process and the fuel properties of hydrocarbons and chemicals produced.

The purpose of this project is to apply a formulation to polymeric turbulent boundary layer flows and, in this way, to make some first, yet decisive, steps in the physics and algorithmics of fully-coupled polymeric boundary layer turbulence.

The research is a co-operation with researchers at California Institute of Technology, and will pioneer superfluid flow-structure interactions with are of key importance in technological and astronomical applications.

Soils, catalysts, tablets, dunes: all are packings of particles. Whether a packing is stable or collapses is a key question in nature and industry. The project uses computational methods to explore what features of a packing’s microstructure makes it stable.

Many applications rely on structured films and membranes, such as selective filters, adsorbents, and biological systems. The project will use computer modelling to analyse how particles with complex interactions aggregate to form films with complex structure and complex time-evolution.

This project will utilise molecular dynamics simulation, exploiting the ARCHIE_WeSt supercomputer at Strathclyde to understand how the inhibitors interact with protein aggregates; how they interfere with the nucleation and growth pathway of the fibrils, and if aggregation can be reversed.

The project will focus on the applications of latest Small-angle X-ray scattering system in CMAC (EPSRC Centre of excellence in continuous manufacturing and crystallisation) to provide mechanistic understanding of interparticle interaction in dense system under repulsive or attractive interactions.

In this project, the student will be involved in an industrial funded project to develop and use spatially offset Raman spectroscopy (SORS) and spatially resolved diffuse reflectance spectroscopy (SR-DRS) for obtaining insight into sub-surface powder drying behaviour.

This project will combine recent theories for the influence of charge correlations on the structure of the electric double layer with a simple quantum description of charge transfer to to develop a new model for electrochemical reactions.

This ambitious project attempts to build a single, unified description of complex fluids that incorporates molecular-level detail but can be applied on a wide range of length and time scales that extends to the continuum scale.

This project aims to develop a new multi-scale simulation model to describe the entire synthesis process of bio-inspired silica materials. The model will then be used to design an ideal material for carbon capture applications.

This modelling and simulation study will investigate processes that occur when foam injection is used to displace fluids from an oil reservoir, and in particular what happens as the foam front changes direction as additional injection wells are brought online.

This project investigates how crystals nucleate and how fluid flows can be used to influence crystallisation, using cutting edge experimental facilities, including high speed high resolution imaging, Brownian microscopy, static and dynamic light scattering and small angle X-ray scattering.

This project will investigate behavioural and performance characteristics of students when working in Problem-Based and Enquiry-based learning activities in order to elucidate the link between the use of these approaches and the development of learner’s autonomy.

This project aims to enhance the understanding of point-source detection of microplastic fragments using spectrophotometry and chemometric methods.

The PhD study will explore conceptual, theoretical, and experimental approaches in biomass utilisation and thermochemical conversion to develop innovative energy solutions and/or processes as well as a circular economy concept for resource recovery.

Quantum Chemistry and Molecular Dynamics calculations will be carried out to explore the mechanism and kinetics of lignocellulosic biomass processing and the conversion of waste into valuable products.

In this project, an integrated system will be designed and developed to ensure efficient generation of liquid transportation fuels whilst maximising the value of biomass into value-added chemicals by controlling structure and functionality as they form.

The project involves the development of a pilot scale reactor with instrumentation that will enable the interrogation and optimisation an electroforming process. Both scientific and statistical techniques will be employed to interpret process data enabling process control.

This project aims to develop embedded optical fibre sensors for polymer electrolyte membrane fuel cells to characterise catalyst degradation mechanisms under realistic operating conditions.

This project aims to develop a new process for hydrogen production using biomass electrolysis.

This project aims to use molecular dynamics simulations to understand how the interaction between filler, coupling agent and polymer influence the composite properties.

This PhD project will explore the design, characterisation and application of exsolved materials for power-to-X energy conversion devices where X can be fuels, chemicals, heat or power, all essential for transitioning to a clean, sustainable energy economy.

This PhD project will develop reversible solid oxide cells based on a newly discovered class of materials, so called exsolved or emergent materials.

The project will investigate Machine Learning and Deep Learning approaches to extract and fuse multiple data streams from multi-sensor setups in chemical and pharmaceutical manufacturing through a combination of experimental work, data analytics and process simulation.

The project will explore the use of hybrid models that combine the advantages of data-driven and physics-based first principles models to enhance the performance of current models for crystal nucleation and growth in chemical and pharmaceutical manufacturing.

The project will contribute to the ongoing efforts in monitoring and improving air quality through the application of machine learning and deep learning algorithms for detection and characterisation of airborne microplastics and asbestos fibres.

The study will assess potential applications of Chemical & Process Engineering on circular nutrient metabolism with focus on urine utilization under the resources available and the constraints existing on Mars.

The study will focus on the current and future challenges of drinking water metabolism in cities to effectively respond in sustainable operational approaches and to support human well-being in urban environments.

The effect of hydrogen on soot formation is a focus of attention for this project since some future energy strategies involve blending hydrogen with conventional fuel. Understanding the effect of hydrogen addition may also help to elucidate the underlying mechanisms of soot formation.

We will develop an innovative technique to study crystal nucleation, using an optical tweezer to generate a localized shear flow in a crystallizing solution, thus triggering nucleation in a known position enabling direct measurement of the growing nucleus.

The aim of this project is to conduct a historical analysis of movement skill assessment in the early years (0-6 years) across the 20th century.

You will work under the supervision of Dr Fraser J. Scott to investigate an aspect of Science Education Research. This will likely be on a topic involving the overlap of Science and Mathematics education, but the specific topic is open for discussion.

You will work under the supervision of Dr Fraser J. Scott to investigate Strathclyde Minor Groove Binders in combination with existing antibiotics. Experimental work will involve in vitro susceptibility testing, toxicity testing, and mechanism of action studies on clinical isolates.

You will work under the supervision of Dr Fraser J. Scott to develop Strathclyde Minor Groove Binders as anti-infective agents. Experimental work will include organic chemistry, but also biochemical (enzyme assays), biophysical (UV-vis, NMR) and biology (in vitro activity) aspects.

This project will explore new methods of constructing C-C, C-N, and C-O bonds using emerging iridium catalysts in order to deliver a variety of pharmaceutically desired organic products. Computationally-based methods will also be used to drive catalyst design, mechanistic understanding, and reaction scope.

This PhD involves the development of analytical methods and their application to investigate the behaviour of microplastic pollutants in the environment. Laboratory and field studies will be used to assess the ability of microplastics to transport potentially toxic elements in terrestrial systems.

The student will investigate and quantify structure/reactivity relationships in nickel catalysis using a range of techniques including organic/organometallic synthesis, physical organic chemistry, and density functional theory, as appropriate.

Developing novel methodologies for portable detection of a variety of illicit substances including but not limited to drugs of abuse, explosives, gunshot residue and / or screening of bodily fluids at crime scenes.

Developing novel methodologies for portable, rapid, point-of-care detection of a variety of biomedically relevant markers for use in biomedical diagnostics

This project will explore new methods of constructing C-O and C-N bonds with iridium-based catalysts. This programme aims to deliver atom economical access to a variety of pharmaceutically-relevant organic products, aided by computationally-driven methods to drive catalyst design and expansion of reaction scope.

This project will explore novel heteroatom-containing substrates in Pauson-Khand cyclisations to construct decorated cyclopentenone products for access to pharmaceutically-desired compounds and natural products. Computationally-based methods will also drive mechanistic understanding, reagent design, and reaction scope.

In this project we would like to use established chemistry from our proof of concept studies in order to form a range of second generation particles exploiting combined therapies of laser released anticancer drugs for pancreatic cancer treatment.

This project will investigate Raman scattering and its variations (surface enhanced (SERS) and stimulated (SRS)) to assess cancer cells and tissue prior to and following treatment with conventional anticancer drugs and particularly new alternative drugs that have shown promise as anticancer agents.

Some enzymes catalyze atom transfer radical polymerizations (ATRP). They represent an environmentally friendly and non-toxic alternative to conventional catalysts. To unlock the potential of bioATRP, advanced polymerization techniques such as electrochemically mediated ATRP and flow chemistry will be investigated.

Improving the efficiency of chemical separations would reduce the impact of industry on the environment. We are looking for a highly motivated researcher to become a PhD candidate in our group and develop porous molecules that show unusual responses to gases, and therefore have potential use in gas separation.

The discovery of new medicines to treat disease requires the identification, understanding and validation of biological pathways and targets. This project resides in the Healthcare technologies theme, aligning with the growth area of Chemical Biology and the areas of Analytical Science and Synthetic Organic Chemistry.

PROTACS and other protein degraders are emerging as promising drug candidates for cancer, but their complex binding modes (simultaneous binding of two proteins) makes them difficult to study. Native mass spectrometry methods will be developed to address this bottleneck in the development of degraders as novel drugs.

The aim of this project is to address the challenge of directly detecting disease biomarker panels in serum featuring target species whose relative concentrations span many orders of magnitude.

This project will develop effective solvers for linear systems in these RBF methods. In particular, we will focus on certain iterative methods (Krylov subspace methods) that start with an initial guess of the solution that is improved at each step.

The proposed project will use a variety of analytical and numerical methods to bring new understanding into a range of real-world problems involving thin films of both simple and complex fluids.

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.

Matrix balancing aims to transform a nonnegative matrix A by a diagonal scaling by matrices D and E so that P = DAE has prescribed row and column sums. Historical motivation for achieving the balance has included interpreting economic data, preconditioning sparse matrices and understanding traffic circulation.

This project will use the theories of liquid crystal fluids to model self-organisation and pattern formation in an active fluid - a type of liquid containing active organisms which interact with the fluid by swimming.

This project will use mathematical models of soil water and the growth of plants. Even for plants with complicated root densities we will look for analytical solutions of the models to help understand plant growth.

The aims of this PhD is to develop the truncated EM method are to study the strong convergence in finite-time for SDEs under the generalised Khasminskii condition and its convergence rate and to investigate the numerical stability of the nonlinear SDEs.

This 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).

Time dependent wave propagation and scattering is important in acoustics, electromagnetics and seismology.

PhD project will synthesize state-of-the-art numerical models, satellite-based remote sensing, and existing bio-physical field observations in order to improve the spatial analyses that go into the production of that Bulletin.

The project deals with VISIBILITY GRAPHS. It will involve numerical work 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.

In this project, you will meet with the challenge of developing and testing an individual based model to simulate the life history and dispersal of Sargassum muticum driven by coastal ocean currents.

The purpose of this project is to conduct a comprehensive extraction and synthesis of all the relevant data for demersal fish species in the Firth of Clyde.

In this project, you will meet with the challenge of developing an individual based model to simulate the growth and dispersal of a highly invasive seaweed (Japanese eelgrass) driven by coastal ocean currents.

There is currently great interest in self-rewetting fluids whose surface tension exhibits a local minimum with temperature. The aim of the project is bring new insight into the understanding of these novel fluids, and hence to harness the properties of droplets of such fluids in a range of technological applications.

Many problems are described by partial differential equations that are too difficult to solve analytically. Numerical solutions must be used, which typically require the solution of linear systems. This project will look at how to solve these linear systems efficiently.

Study permutation tableaux such as the Le- and EW-tableaux, their connections to Abelian Sandpile Model and Asymmetric Exclusion Processes, and the connection between these two models afforded by the tableaux.

Graph representations became crucial with the advent of the computer era for storing graphs in computer memory. However, graph representations, e.g. those involving patterns in words, are also useful in solving problems on graphs as they may allow transferring a graph problem to that on other objects hence solving it.

To ensure that a person taking any route in a city has the same experience, e.g. seeing a city map, we need methods to cover the routes without over-deploying resources. We will use tools in Graph Theory and Combinatorics to optimally deploy resources across a city to have maximum effect on those navigating it.

Liquid crystals are fluids that show local orientational order. The interplay between orientation and flow in these substances is very intricate and can lead to interesting macroscopic phenomena, many of which are not yet fully understood. This project will study such phenomena using mathematical and numerical models.

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.

Effective methods have been derived for dividing a network into coherent communities using spectral information obtained from the network. Biclustering has received far less attention. We will develop new methods and analysis for this problem, starting from recent work using a bistochastic representation of a network.

The student will be part of a project which addresses the challenge of modelling one of the most important environmental problems currently affecting people's health, urban air pollution.

The student will be part of a project which addresses the challenge of modelling one of the most important environmental problems currently affecting people's health, urban air pollution.

The profound is deep and sublime; activities such as religion, altruism, wisdom that give meaning to life. Information such as poetry, religious texts, life stories are often used to create profound activities that help us understand how to live a good life.

We are looking for PhD Students interested in making search engines (and machine learning in general) fairer, more transparency and explainable.

This project is focused on developing and applying next generation detectors for the scanning electron microscopy techniques of electron backscatter diffraction (EBSD) and electron channelling contrast imaging (ECCI).

A project to develop and use a new super-resolution optical microscope to obtain very high spatial resolution images of fluorescently labelled live cells.

Motivated PhD candidates, ideally with a background in laser and/or beam driven plasma wakefield acceleration are required to help lay the foundations in the quest towards 5th generation light sources and ultra-compact electron accelerators - the time-resolved microscopes of the 21st century.

In this PhD project – funded by the Leverhulme Trust and in collaboration with Dr. Sonja Franke-Arnold at the University of Glasgow – you will demonstrate storage and processing of OAM information in a rubidium vapour.

PhD position available to undertake frontier research in nanotechnology of noble metal nanoparticles.

An EPSRC funded studentship in theoretical quantum information, specifically the relationship between decoherence, non-classicality, and the efficacy of quantum information tasks.

This PhD project aims to develop a comprehensive suite of tools and techniques that will enable superresolution imaging of nanodiamonds in living tissue, with a particular emphasis on imaging neurons.

The project develops, optimises, and strategically compares accurate mathematical models for the generation of frequency combs in micro-resonators in a close connection with the experiments performed at NPL in Dr Del'Haye's laboratory.

A fully-funded PhD studentship is available in high power laser-plasma physics, working within a vibrant team of experimentalists and theoreticians, to investigate the onset of a new regime of high-field relativistic plasmas.

PhDs are available in an exciting and challenging research area, with a vibrant group of experimentalists and theoreticians developing and applying ultra-compact accelerators and x-ray sources based on laser-plasma interactions.

The project will study the properties of amplifying and nonlinear films both analytically and numerically. Collaboration with an experimental team at the University of Glasgow will also be exploited.

This project involves different microscopic techniques to investigate semiconductor heterostructures and light-emitting diode devices, performed on our suite of scanning electron microscopes, providing information on material properties at length scales ranging from nanometres to centimetres.

This PhD will investigate novel ways to laser cool two-electron atoms all the way to Bose-Einstein condensation – to provide new insight into the formation of condensates, and potential applications in precision measurements.

A fully-funded position to undertake research in the ground-breaking field of quantum sensing and measurement, after the first year specialising in Magnetometry.

A fully-funded position to undertake research in the ground-breaking field of quantum sensing and measurement, after the first year specialising in Atomic Clocks.

A fully-funded position to undertake research in the ground-breaking field of quantum sensing and measurement, after the first year specialising in Atom Interferometry.

We focus on new nonlinear regimes with input powers so low that they enable all-optical processing and the exploitation of the fundamental advantages of quantum technologies at the nanoscale.

This project will develop chip scale optoelectronic systems through the 3-dimensional printing of nanoscale building block components such as nanolasers and thin film electronics.

Diamond is an exciting and enabling material of laser engineering. This project will aim to exploit diamond directly as a laser gain material so as to fully exploit its excellent thermal and mechanical properties.

Advances in microscopy allow imaging on scales ranging from single molecules to whole organism. This project involves developing a microscope that will allow images of whole invertebrates (likely C. Elegans nematode worms) be correlated with nanoscopic (super-reolution) images of sub-cellular regions within them.

We invite outstanding and motivated students to join our team, for research on ultracold atoms in optical lattices. We use a quantum-gas microscope to measure the dynamics of ultracold fermions at the single atom level.

This project is focussed on advanced modern image analysis and pattern recognition methods to study the microscopy and spectroscopy of semiconductor structures and devices. Developing automated and robust methods to look at images and video will revolutionise this area.

We explore nonlinear quantum regimes of the coupling between light and matter for ultra-low power micro and nano-lasers. These are promising candidates to achieve high efficiency, high speed, and a small footprint.

Two PhD positions for UK and EU students are available funded by University of Strathclyde and collaboration partners to work on laser-plasma based particle accelerators and plasma photonics for high power lasers via theory and large scale of numerical simulation.

In this project we will investigate various approaches for on-demand engineering of trapped spin states in charged quantum dots through a series of coherent control experiments that will explore how the different approaches affect the performance of all optically operated universal single qubit gates.

This project in quantum optics will analyse practical quantum radar and lidar scenarios with realistic detectors in a jamming/spoofing environment.

This project focuses on the realisation of quantum phenomena in commercially-compatible electronic devices, such as transistors and diodes in silicon carbide. The main goal is to couple electron spins to electromagnetic radiation, in order to manipulate and read quantum states.

Gallium oxide is an emerging semiconductor offering promises for applications in ultraviolet optical devices. The project aims to improve our understanding of the material, elucidate the mechanisms leading to its optical properties, and exploit the findings to produce better devices.

This project will develop new numerical techniques for studying many-body quantum systems far from equilibrium, exploring the possible phase transitions which can be realised.

Modelling of laser light propagating in micro-ring resonators in collaboration with experiments performed at the Max Planck Institute for the Science of Light in Erlangen (Germany). Applications of these devices are in atomic clocks, quantum technologies, telecommunication, GPS and integrated photonic circuits.

Free-Electron Lasers (FELs) use electron beams produced by particle accelerators to generate intense electromagnetic radiation from microwaves into the hard X-ray, which is of particular interest to a wide range of users. This project will look at developing new types of FEL output further enhancing their applications.

Immunology, infection, diabetes, mast cells, autoimmunity, obesity Cellular Basis of Disease

The vision of this PhD project is to establish whether there is a universal mechanism for biological ammonium transport. Beyond the elucidation of a central biological process, this work will have important medical implications, offering a mechanistic explanation to correlate Rh malfunction and associated diseases and

Cellular basis of disease, membrane trafficking

Molecular Biology Microbiology Genomics Antibiotic Resistance Gene Regulation Transcription Chemical Biology Medicinal Chemistry

CLXL12, cancer, Nuclear factor kappa B, signalling, molecular. Cellular Basis of disease/Drug discovery

Advanced manufacturing (Daniel Markl), Drug Delivery (Health and Wellbeing – Z Rattray)

Leishmaniasis is a serious health threat. Current there is no clinical vaccine. This project will build on pervious studies to develop a recombinant protein vaccine to protects against leishmaniasis.

Cardiovascular and Metabolic Disease Cell Biology

The student will have the opportunity to learn a wide range of multidisciplinary techniques: synthesis and characterization of the nanomedicines, cell culture, in vitro analysis techniques (i.e. flow cytometry, cytotoxicity assay, confocal microscopy) and in vivo analysis.

Immunology, immunopharmacology inflammatory/ metabolic cell pathology

Secondary metabolomics; marine natural products; antibiotics; anti-cancer drugs; NMR; MS; drug discovery; multivariate analysis

Microbiology and Industrial Biotechnology; Streptomyces; Antimicrobial resistance; natural product biosynthesis

Marine microbial chemistry Actinomycetes Marine natural products Specialized metabolism Comparative metabolomics Antibiotic Discovery

Drug delivery and formulation; biopharmaceutics; women’s health

Microbiology and Industrial Biotechnology, antibiotic-producing bacteria, genomics, genetics

Drug utilisation research; adherence; clinical effectiveness; Antimicrobial Resistance; antimicrobial stewardship; Health Service Research

Drug development; Drug discovery; chiral synthesis, organic synthesis, decracemisation by crystallisation, Veidma Ripening, medicinal chemistry, single crystal X-ray crystallography, XRPD, HPLC, pharmaceutical analysis

Neuroscience, immunology, multiple sclerosis

Materials & Manufacture. High-pressure; co-crystals; polymorphism, diffraction, spectroscopy.

Neuroscience, Neurotechnology, Ageing, Machine Learning

Helminth, parasite, drug therapy Cellular Basis of Disease

Inflammation, microbiome, helminths, mast cells, immunology, cytokines, costimulation Cellular Basis of Disease

Cardiovascular and Metabolic Disease Cell Biology

Advanced manufacturing (Y Perrie); Drug Delivery (Health and Wellbeing – Y Perrie, Z Rattray); Particle Characterization (Measurement and Enabling Technologies, Z Rattray)

Advanced manufacturing (D Markl), Drug Delivery (Health and Wellbeing – Z Rattray)

Cellular Basis of Disease (Health and Wellbeing- Z and N Rattray), Metabolomics (Health and Wellbeing, Measurement and enabling sciences- N Rattray), Drug Delivery (Health and Wellbeing – Z Rattray)

Cardiovascular and Metabolic Disease Cell Biology

Cardiovascular and Metabolic Disease Diabetes Cell Biology

Materials & Manufacture. High-pressure; co-crystals; polymorphism, diffraction, spectroscopy

Leishmaniasis is a serious health threat. We have preliminary data to show that light can have anti-leishmanial activity and the aim of this project is to design a medicinal device that can be used to treat cutaneous leishmaniasis.

Leishmaniasis is a serious health threat. Diagnosis can be completed using different techniques but the gold standard is identifying parasites in stained samples from infected individuals. In this project we will look at using machine learning in parasite diagnosis

There are 1.3 million new cases of lung cancer per year world-wide and it has one of the lowest survival rates. In this project we will reformulate an existing cancer drug into a drug delivery system to target the drug to the cancer cells.

Neuroscience immunology neurodegenerative diseases

Neuroscience, Neurotechnology, Ageing, Machine Learning

Computational Biology Bioinformatics Microbiology (genomics, classification metabolism, and epidemiology) Microbe-host interactions Modelling of biological systems Software and algorithm development

Protein kinase, Leishmania, signal transduction, protein-protein interaction. Cellular Basis of Disease/Cancer and Inflammatory Disease

Protein kinase, Leishmania, signal transduction, protein-protein interaction. Cellular Basis of Disease/Cancer and Inflammatory Disease

Cellular Basis of Disease: Neurodegeneration, Cell Biology, Molecular Genetics

Drug and stem cell delivery using biopolymers

Pharmacognosy, Natural Products Chemistry, Medicinal Phytochemistry

Cardiovascular and Metabolic Disease Cell Biology

Neuroscience & Mental Health MKP-2, synaptic vesicles, neurotransmitter, synaptic transmission

Neuroscience & Mental Health proteinase-activated receptor 2, Alzheimer’s disease, β-amyloid cytokines, major depressive disorder, treatment-resistant depression

Research group: Neuroscience & Mental Health Key words: proteinase-activated receptor 2, inflammation, cytokines, major depressive disorder, treatment-resistant depression.

Organic & Medicinal Chemistry

The project will explore novel strategies to study cardiac cellular metabolism using isolated primary adult cardiac cells and the use of spheroids.

computational biology; comparative genomics; bioinformatics; systems biology

A three-year Economics PhD scholarship in collaboration with the Competition and Markets Authority (CMA) for candidates who wish to explore the loyalty penalty from an industrial organisation perspective.

Developing and evaluating new and emerging artificial intelligence (AI) methods to extract useful information from unstructured datasets, namely earnings call transcripts.

The goal of this PhD project is to incorporate Topological Data Analysis (TDA) into a stock selection framework with evaluation in an equity context, by combining it with more traditional unsupervised machine learning methods.

Utilising new and emerging Artificial Intelligence (AI) methods to study research questions on Financial Technology including but not limited to Ontologies and Knowledge Representation within this domain.

This scholarship welcomes applications that study management and policy aspects of science, innovation and entrepreneurship by employing advanced data science approaches and/or utilising new data sources.

This is an opportunity for a fully funded (stipend and fees) to work together with Dr Tapinos and Dr Makhmadshoev. We invite applications, which should include a proposal, employing a qualitative research approach, on the areas of institutional uncertainty, strategy, internationalisation and foresight. The project will