You can study an MPhil over the course of one year or a PhD over the course of three years here in Scotland.
You also have the option of studying a PhD in Saudi Arabia over three years, four years or five years.
Part-time study is available too.
You can study either option in any of our eight research groups:
- Computer Security
- Digital Health & Wellness Group
- Strathclyde iSchool Research Group
- Mathematically Structured Programming
- The Mobiquitous Lab
- Similarity & Metric Search
- Software Systems
The Digital Health & Wellness research group in the Department of Computer & Information Sciences at the University of Strathclyde has been awarded eight Masters scholarships by the Digital Health & Care Institute (DHI) under the Scottish Funding Council (SFC) Highly Skilled Workforce (HSW) programme.
Find out more about the scholarships.
Postgraduate Certificate in Researcher Professional Development (PG Cert RPD) programme
As part of your PhD degree, you'll be enrolled on the Postgraduate Certificate in Researcher Professional Development (PG Cert RPD).
This certificate is designed to support you with your research and rewards you for things you'll do as a research student here.
It'll help you improve skills which are important to professional development and employability:
- the knowledge and intellectual abilities to conduct your research
- the personal qualities to succeed in your research and chosen career
- the standards, requirements and conduct of a professional researcher in your discipline
- working with others and communicating the impact of your research to a wide range of audiences
All you have to do is plan these activities alongside your doctorate, documenting and reflecting your journey to success along the way.
Shape Optimisation of Hydraulic Devices
Development and application of optimisation methods and tools to find the best shape of existing hydraulic devices – or some of their components - to maximise one or more predefined perfomance based on CFD/FEM modelling
Topology Optimisation of Hydraulic Devices
Development and application of topology optimisation methods and tools to find the best configuration of innovative hydraulic devices – or some of their components - to achieve the best structural design
PhD New Hyperspectral Imaging Processing Techniques to Detect the Early Onset of Plant Disease
A 36-month full-time, fully-funded PhD, supported by the University of Strathclyde, focusing on developing new Hyperspectral Imaging Data Processing Techniques for the agri-tech sector.
Deadline:25 May 2018
PhD Power Systems Dynamic Security Assessment using machine learning.
This 42-month full-time, fully-funded PhD, supported by EPSRC focusing on the area of power system stability and dynamics using powerful machine learning tools that enable informative and fast online dynamic security assessment.
Deadline:30 June 2018
PhD Effective EEG analysis for advanced AI-driven BMI/BCI systems
A 36-month full-time, fully funded PhD project aiming to analyse and understanding EEG signals and how they are linked to our human brain activities. Modelling such mechanisms can further help strengthen BCI and BMI systems.
Deadline:31 August 2018
Industry Funded PhD Scholarship on Trust and Transparency: Understanding and Communicating with Machine Learning and Artificially Intelligent Agents
This Industry Funded PhD Scholarship will explore how people trust and understand the actions and decisions of Artificial Intelligence (AI) and Machine Learning (ML) agents and develop methods to communicate and interact efficiently and effectively with such agents.
Deadline:31 July 2018
Team-Based Agent-Human Collaboration in High Pressure Information Environments
This EPSRC iCase PhD project with British Aerospace Engineering (BAE) will blend human computer interaction (HCI) with Machine Learning (ML) to develop artificially intelligent agents that can collaborate effectively with teams of humans to ensure success in high pressured and stressful environments.
Deadline:1 July 2018
Algorithmic Bias in Search Engines
We are looking for PhD Students interested in making search engines (and machine learning in general) fairer, more transparency and explainable.