Investing in excellence: studentship opportunities - Autumn 2022

We are no longer accepting applications for this studentship. If you have any enquiries, please email

The University of Derby has an opportunity for a full-time postgraduate research studentship in Computer Science, Data Science and Data visualisation area of research.

Studentship project title: Computer Science, Data Science and Data Visualisation

Qualification type:Location:Funding amount:Hours:Closes:Interview:Start date:
MPhil/PhD Derby, UK £16,062 stipend per annum for a maximum of three years + UK home tuition fees (£4,596) Full-time Friday 24 June 2022 4 - 15 July 2022 September/October 2022

The successful applicant will receive a maintenance stipend (based on the minimum stipend defined by UKRI, currently £16,062 for the academic year 2022/23) and home MPhil/PhD tuition fees (£4,596) for a maximum of three years. 

International students will be responsible for paying the difference between international and UK tuition fees* - a difference of approximately £10,000 per annum.  

Costs associated with practical work, field work, subject specific training, conferences etc. will not be covered directly by this studentship opportunity, but please discuss with supervisors whether any additional provision is available.

Please note, if your application is successful and you are assessed as Overseas for fees purposes, you will need to pay the difference between the Home fees and the EU/Overseas fees.

The intended intake period is 26 September - 7 October 2022, or the next available intake.

The successful applicant will be expected to complete their MPhil/PhD within 3 - 4 years on the MPhil/PhD route, contribute to the College of Science and Engineering REF submission and get involved in the wider research activities of the College. 

Applicants will become part of a friendly and welcoming team and will be supported and managed by their supervisors. 

The vacancy details are as follows: 

Available Projects

Within the College of Science and Engineering, this studentship can be in any of the following areas: 

  1. Affective Computing in Virtual Reality Systems: Multimodal data fusion approaches for real-time user understanding

    Virtual Reality (VR) is currently used in a range of problem domains that are intended to have a psychological impact on users. Measuring this impact in terms of the user’s “affective state” tells us much about their in-simulation experience; e.g., if they are happy or sad, anxious, or relaxed. Through a VR use case, this PhD will explore and validate an affective state solution that detects the experience of users in real-time.

    Please contact Dr Tom Hughes-Roberts at if you wish to discuss this project in advance of applying.

  2. A novel unified framework for precision medicine in heterogeneous big data workflows

    The global market for personalized medicine (PM) is continuously growing and by end of 2022 is expected to be 28 billion USD. With advent of PM, the demand for adapting diverse workflows is a growing concern in different domains with stakeholders having diverse capabilities. This research work enables stakeholders to collaborate through a unified framework and produce knowledge contents reflecting collaborative intelligence of data and domain knowledge.

    Please contact Dr Maqbool Hussain ( if you wish to discuss this project in advance of applying.

  3. IoT adoptable Post-Quantum Signature Schemes for Distributed Ledger Technologies

    The developments in quantum computing supremacy have challenged many security landscapes. This research will focus on developing a post-quantum digital signature scheme suitable for IoTs. A secondary goal of the research is to design a blockchain which can incorporate the developed signature scheme for realising various new and existing use cases in IoTs. 

    Please contact Dr Abid Khan ( if you wish to discuss this project in advance of applying.

  4. A study into the relative strength of network parameters, with a motivation in data science

    Do you get excited about graph theory, algorithms and data science? Do you feel thrilled to witness aesthetically beautiful mathematical theory intertwining with powerful real-life applications? This project seeks to refine the known hierarchy of graph width-parameters measuring the structural robustness of networks. Some parameters, if bounded for a set of networks, imply efficient algorithms for infinitely many computational problems, including efficient route-planning and restricting the spread of epidemics. We find close parallels between graphs, permutations and words. The work would contribute to journals and conferences in multiple topics: graph theory, combinatorics, data science, theoretical computer science and permutation patterns. 

    Please contact Dr Nicholas Korpelainen ( if you wish to discuss this project in advance of applying.

  5. Novel AI-based Cyber Attack Prediction Methodologies

    Cyber Attack Prediction is a key concept in combating cyber attacks against critical infrastructures. In this PhD project, we will investigate state-of-the-art graph-based AI algorithms targeting user sessions used for cyber reconnaissance. The project will be carried out in close collaboration with NVIDIA, Belfast by using their research infrastructure.

    Please contact Professor Fatih Kurugollu ( if you wish to discuss this project in advance of applying.

  6. Contextual Security Barriers in the Context of Federated Learning

    Federated Learning architectures are a distributed machine learning approach that integrate data transfer, data aggregation methodologies, model training, and parallelism, to enable collaborative machine learning that does not compromise sensitive information.  However they still contain vulnerabilities. This  project focuses on establishing a Federated Learning empowered secure environment by investigating the security and privacy threats within a given Federated Learning environment.

    Please contact Dr Aaisha Makkar ( if you wish to discuss this project in advance of applying.

  7. Artificial General Intelligence (H-AGI) for Achieving Machine Creativity

    Imagine a computer  authoring a poem for a favourite singer, or creating a masterpiece painting based on your holiday photos? Such creativity is a challenge for current Artificial Intelligence (AI) techniques. This project will investigate approaches to developing creative AI technologies using a human guided approach.

    Please contact Dr Harry Yu ( if you wish to discuss this project in advance of applying.

To apply 

Completed applications should be submitted via our online application system quoting funding reference: CoSE_PGRS_Data_SEP22

Closing dates for applications: 12.00 pm Friday 24 June 2022

Interviews: 4 - 15 July 2022 

If you have not been invited for an interview by the interview date, please assume your application has been unsuccessful.  

Find out more about our research degrees.

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