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10 PhD Studentships

Edinburgh Napier University - School of Computing

Edinburgh Napier University is ranked the top modern University in Scotland in the 2022 Times World University Rankings. The School of Computing is highly regarded as one of the UK's largest computer science departments and has invested recently heavily in research in terms of both staff and facilities to conduct world class research in a wide range of disciplines.

In the 2021 Research Excellence Framework (REF), the School was ranked 3rd in Scotland in terms of Research Power – and in Computer Science and Informatics we scored a perfect 100% four star for our research impact.

As part of our recent significant investments in research, we have recently recruited additional academics with outstanding research capabilities.

The investment in research is continuing with 10 fully funded 3-year PhD studentships being made available. Applications for this are now invited from UK applicants.  The studentship will cover full UK tuition fees and will include a standard living allowance at the RCUK rate (Currently £15,609 pa).

The studentship is expected to start in October 2022 or March 2023.  All applications must be received by 13th July 2022 (see details below). Those who have not been contacted by 7th August 2022 should assume that they have been unsuccessful.

The School of Computing is truly international, with staff and students coming from across the globe.  It undertakes high quality research across a broad range of areas, including but not limited to: artificial intelligence; big data, cyber-security; e-Government; e-Health; edge computing, future interactions; Internet of Things; interactive graphics and simulation; information science; information society; information visualization; networks & distributed computing; social informatics, software engineering & systems and urban interaction design.

Applications in these areas are welcome. The priority will be particularly given to the following topics:

Multimodal Applications for Cognitive Differences

Contact for more details: Dr John McGowan:

Previous studies have demonstrated physiological as well as psychological benefits of interactive multimodal systems through listening to and making music, the use of voice, or gestural interactions. Further development of accessible applications for people with cognitive differences could encourage shared experiences with friends and family, increasing their effective therapeutic capabilities, whilst helping to manage stress. This PhD project will employ a User Experience and Interaction Design approach to investigate, develop, and evaluate shared interactive multi-modal applications, including vocalisation and gestural parameters.  This work builds on the expertise of staff at ENU School of Computing. 

Computational Sustainability

Contact for more details: Dr Brian Davison:

Computational Sustainability is an interdisciplinary field of research that applies advanced computing techniques to problems of sustainability. Projects are typically grounded in a domain of application such as renewable energy, precision agriculture, circular economy, etc. and often benefit from collaboration with industry. Computational approaches can include machine learning, sensor networks, agent-based systems, etc. The range of potential topics is very wide, and proposals are invited for projects with three specific features: (1) An explicit focus on one of the 17 UN sustainable development goals (SDGs) (2) A clearly defined problem in a specific domain of application (3) A proposed computational approach

IoT enabled privacy-preserving deep learning for multi-modal assistive and healthcare applications

Contact for more details: Dr Kia Dashtipour:

The next generation hearing aids are focusing to realize more intelligible audio by gathering the data in the form of audio-visual to make the hearing aids more effective in the noisy environments. In order to achieve this goal, deep learning techniques play an important role for the processing of data collected from the hearing-aid devices. Since the computational complexity of the hearing-aid devices is low, therefore this data must be processed either on edge or cloud which raises the privacy concerns for the sensitive user data. The project aims to develop methods based on wireless sensing, natural language processing (NLP) and IoT enabled privacy-preserving deep learning for multi-modal assistive and healthcare applications.

Safe City Sound Map 

Contact for more details: Dr Rod Selfridge:

This project aims to create a sound map indicating where and when women feel harassed or intimidated as well as where they are happy and safe. Using mobile technology, women will be able to anonymously indicate their feelings about a specific location and why. Soundscapes representing these emotions through augmented reality, can allow others to empathise and drive social change. Harassment and intimidation are an everyday experience for women in public places and are believed to be under reported. Through sound maps it would be possible to educate and enlighten others to these feelings to improve the shared city space. 

Image-based plant analysis for sustainable agriculture

Contact for more details: Dr Valerio Giuffrida:

Image-based plant phenotyping allows the quantification of traits (e.g. leaf area, number, colour) reflecting plant performance non-destructively. This approach helps in deciphering the complex genetic-environment interactions influencing its performance and finding the best-adapted crop varieties to local environmental constraints for sustainable agriculture. Deep learning methods are necessary to speed up analyses from large image datasets. For this PhD project, we are looking for a motivated student with expertise in deep learning to develop classification, segmentation, and regression models for plant image analysis. The successful candidate should be experienced with a major deep learning library for python.

Recommender System Support Treatment Personalisation for Digital Health Therapy

Contact for more details: Dr Shufan Yang:

Recommender systems have the potential to improve the user experience of managing chronic disease. Personalised recommendations can help users to identify therapy tasks that they find most enjoyable or helpful, thus boosting their engagement with an optimised service. Using open accessible datasets, this project aims to develop collaborative filtering algorithms that can predict how much a user will benefit from a new therapy task with greater accuracy than a simpler baseline algorithm that predicts the average rating for a task and it can be adjusted for the biases of the specific users and specific tasks.

The Limits of Digital Image Authentication and Identification, and how to move forward

Contact for more details: Dr Sean McKeown:

We live in a multimedia-centric society, where images and video are increasingly leveraged in social media, news, and entertainment. The ubiquity of multimedia files, and the accessibility of modern creation and editing tools, has created a very difficult environment in which to ascertain the veracity, or integrity, of such media. This project seeks to ascertain the current limits of digital image processing tools, and to work towards general solutions to the problem by characterising contemporary “attacks” on image integrity, and to identify mechanisms to overcome them.

Artificial Intelligence for reliability enhancement in digital healthcare

Contact for more details: Dr Sana Ullah Jan:

The digital healthcare devices face faults and breakdowns sometimes which causes serious consequences for patients. This project will focus on developing Artificial Intelligence-based techniques to detect the patterns in the initial phase of these unwanted situations. By predicting these vulnerabilities in time, alternative measures can be put in place to avoid unwanted serious consequences. The project will include different phases of collecting and analysing data from healthy as well as faulty nodes using data visualization techniques to highlight key insights about it. These key findings will be used to design the algorithms and techniques to countermeasure the target situations.

Multimodal Conversational AI for Physical task Supervision

Contact for more details: Dr Yanchao Yu:

This project aims at exploring/evaluating the state-of-the-art models/technology to interactively supervise the robot/human users to complete physical tasks through human, daily conversation in Natural Language. The agent can learn the sequential actions, movements and instructions from either unstructured videos, demonstrations or even pure text-based user inputs. The project leads to but is not limited to several directions, e.g. automatic evaluation of human actions, video-based learning framework, and interactively video-language grounding.

Characterising the differences between human- and machine-generated language 

Contact for more details: Dr Pete Barclay:

Research is needed to understand the differences between human- and machine-generated text.

This includes both predictive models that might be used, for example, to identify bots on social media sites or software-generated essays, and also linguistic analyses that allow us to explain the weaknesses of current models.

While neural language models can generate remarkably fluent and coherent text, concerns have been raised about shortcomings in their robustness, and potential unethical uses.

Current literature treats bot-detection and cognitive plausibility as two separate domains, but we would seek to uncover synergies between these areas.

What now? Understanding the impact of higher education policy

Contact for more details: Dr Debbie Meharg:

Higher Education is changing and understanding the complex offering of colleges, universities and apprenticeships can be difficult but has never been more important.  This PhD will provide an in-depth understanding of policy and practices which promote equality, diversity and inclusion in education.  Utilising mixed methods this research aims to develop an evaluation framework to better understand the impact of higher education provision. By working with current students, future student, practitioners and policy writers to gain insight and provide recommendation to improve outcomes and ensure the voice of pupils, students and parents are heard by policy-makers.

Researching online human information behaviours       

Contact for more details: Dr Frances Ryan:

This research will focus on information sharing and use in online or digital environments as it relates to everyday life and “lived” or real-world experiences. Proposals should consider issues of reputation and identity, determinations of trust, or related themes in the context of the information people share (or self-censor) online, as well as motivations for sharing or censoring information. We would be especially interested in proposals that use qualitative research methods to consider online information sharing behaviours related to (1) health and wellness or (2) significant life events and experiences.

User centred approaches to supporting digital literacies and online information systems use 

Contact for more details: Dr David Brazier:

Uptake of digital services assumes suitable digital literacy proficiencies and access for those who need such services. Gauging the veracity of the information we interact with or navigating essential platforms such as benefit applications; outcomes can be subjective. They are often dependent on a user’ experience and capabilities in identifying when enough information has been obtained or a task has been resolved. There remain opportunities to support users from a systematic and educational perspective. A PhD candidate could explore these opportunities in a wide range of contexts, to be determined along with the supervisory team, to establish user focused solutions

Information governance and the digital environment 

Contact for more details: Dr David Haynes:

The studentship will investigate regulation and governance of the digital environment. The focus of the research will be: impact of the digital environment on the privacy and safety of individuals and on their online behaviour. Digital literacy and empowerment are specific research areas in the Social Informatics research group. Potential research topics include (but are not limited to): Ontology of online risk, Metadata for information governance, Online safety and the metaverse, Digital empowerment and social media. 

Organisational Learning and Agile Coaches                               

Contact for more details: Dr Pritam Chita:

There are currently many agile coaches and those tasked with mentoring remits within the IT function. Little is known about the involvement and role of agile coaches regards the adoption and deployment of agile methods with inconsistent approaches and varying successes.  

This project will research how organisations facilitate the learning of agile methods using agile coaches. It will examine agile coach selection, coaching activity and analyse how organisations evaluate the results of their agile methods adoption/improvement endeavours, and the contribution of the agile coach. 

Compiler support for mixed-precision AI accelerators               

Contact for more details: Dr Stefano Cherubin:

Layout of data, its numeric precision, and its transfer costs are the focus of recent AI accelerator architectures. However, comparing the precision across different representations is a difficult task and automated solutions are required. The new trends push towards exploiting custom-defined data types, and poses new challenges for the precision tuning tools, which need to balance new precision requirements. There is room for improvement in the current state-of-the-art toolchains. From code analyses to code verification, multiple areas are touched by this research. C++ and code optimization skills will be beneficial to support ongoing prototype development.

Zero Trust Internet of Things                                 

Contact for more details: Dr Matthew Broadbent:

Remote sensing platforms are used to record information from many different sources. Whether this be usage of a space or safety critical environmental monitoring, the accuracy and authenticity of data is vital. This data can also be personally identifiable or business sensitive, making secure transmission of the information important too. As such, this PhD will investigate a Zero Trust approach to building the Internet of Things. This security model assumes that every device, user, and network is a threat. This work will apply this in a challenging setting where resources are scarce, technologies are diverse, and the risks are high.

Secure and privacy-preserving solutions for IoT networks

Contact for more details: Dr Baraq Ghaleb:

While the emergence of the Internet of Things has facilitated the deployment of several applications, it has widened the attack surface as IoT devices are easy to attack due to their power and/or computing constraints. Several IoT technologies have been developed recently, however, their security aspects have not been thoroughly investigated making it easy to compromise their availability and privacy. Consequently, there is a clear need to investigate the security of such technologies to uncover any unknown vulnerabilities and then build on such investigation to develop effective countermeasures, thus facilitating more secure deployment of IoT applications.

Mobile Edge Solutions for Energy and Performance Improvement in Wireless Sensor Networks

Contact for more details: Dr Craig Thomson:

A project to research the use of Mobile Edge solutions to influence the network performance and/or energy consumption in Wireless Sensor Networks (WSNs). The aim being to implement solutions in Mobile Edge devices – potentially robots or Unmanned Aerial Vehicles (UAVs) - such that these devices may, potentially, utilise Machine Learning techniques in order to influence network performance in real time. This research has potential to influence IoT protocols at both the Network and MAC layers, in addition to affecting battery consumption in sensor nodes.

AI enabled orchestration of next generation Internet-of-Things systems in the Cloud-to-Things computing continuum

Contact for more details: Dr Amjad Ullah:

The scope of this research area includes the use of novel AI methods to address problems from the Cloud-to-Things computing continuum with a particular focus on case studies from smart cities and industry 4.0. Some of the key focus points include: Automated orchestration and Dynamic resource management of IoT systems, model-driven specification for describing smart systems to enhance interoperability across different resource providers, efficient connectivity and run-time management of volatile Non-cloud (Fog/Edge) resources, context-aware automated deployment and runtime management of microservices, distributed context-aware run-time reconfiguration decisions to support orchestration.

Applied Machine Learning and Cybersecurity

Contact for more details: Dr Christos

It’s impossible to deploy effective cybersecurity defence layers without relying heavily on Machine Learning (ML). With ML, cybersecurity systems are in position to analyse patterns and learn from them, to efficiently help them prevent similar attacks. Additionally, we should never forget that adversaries in the arms race with defenders, always employ new solutions to attack the machine learning models. The latter activities being manifested during the past five years, demand from the research community robust algorithms against adversarial examples. In short, the combination of ML and cybersecurity can be the cornerstone on which we can built robust and efficient systems

Defeating Complex Families of Malware Using Evolutionary Based Adversarial Learning

Contact for more details: Dr Kehinde Babaagba:

Malicious attacks account for a significant portion of attacks to information assets and computer networks in organisations today. More specifically, dangerous groups of malware that transform their code structures between generations such as metamorphic malware, provide a greater attack surface for the perpetuation of cybercrimes. My research involves the use of evolutionary based adversarial learning approaches in defeating complex and dangerous malicious groups such as polymorphic and metamorphic malware. This involves the use of adversarial learning strategies in the generation of malicious mutants and the augmentation of training data with the produced mutants to improve the classification of such families of malware.

Mixed Reality and Hybrid Experiences, with an emphasis on Meaningful experiences and Playful interactions across several contexts

Contact for more details: Dr Dimitrios Darzentas:

This research includes an interdisciplinary approach to the design, implementation and analysis of Mixed Reality and Hybrid Experiences, with an emphasis on Meaningful experiences and Playful interactions across several contexts, including Cultural Heritage, Wellbeing, Sustainability and Entertainment. Combining elements of New Materiality and User-centred Design with Ubiquitous and Embodied computing and rapidly evolving technologies such as Augmented and Virtual reality, there is fertile ground for research into meaningful experiences, services, and products across a broad front. Students who are interested in any of the above challenges are very welcome to get in touch.

Natural Language Generation in Low-resource settings

Contact for more details: Dr Dimitra Gkatzia:

Natural Language dialogue systems such as personal assistants have become prevalent in everyday life, offering support for decision-making, education, health and entertainment. Development of such systems requires access to many examples of dialogues, which can be hard to attain in many domains. Current response generation techniques are heavily based on pre-specified templates that limit language coverage. This PhD will address these interlinked challenges by proposing natural language generation techniques that can learn from limited resources by reusing the knowledge learnt in other data-rich domains, similar to how the human brain learns new skills efficiently by building on prior knowledge.

Sound design for augmented embodied interactions in virtual environments

Contact for more details: Dr Balandino Di Donato:

Sound design can play a crucial role in supporting immersive experiences and fostering seamless ‘natural’ embodied interactions with the virtual and real world. Interactions with the virtual are fostered through the continuous development of devices (wearables and hearables) and their applications in interactive experiences (games, exhibitions, installations, tours....). Although technologies enable interaction with the virtual through bodily gestures, there is a paucity of auditory feedback to fully support these interactions at the intersection between the real and virtual. We invite applications that explore how sound design can support embodied interactions in virtual environments (AR/VR/MR/XR).

The role of digital technologies in sustainability – empowering citizen engagement with user-centred interventions

Contact for more details: Dr Ashley Morton:

New digital technologies and interactive experiences offer the potential to help enhance our day to day lives and mitigate many of the challenges our society faces today, but many of these are reliant on end user acceptance. Many potential solutions fail to achieve the expected results or engagement required for significant impact. Through user-centred approaches, technologies, experiences, and solutions can be designed to fit the end-users needs. My research focus is on understanding end-users within the context of digital technologies; energy use & awareness; smart cities & citizen engagement; sustainability; behaviour change; and user experience design.

Candidate Profile

Interested applicants should:

  • Have a first class Honours degree or Masters degree at Distinction level, in a discipline relevant to the area of study.
  • Prove highly motivated to tackle challenging research problems
  • The potential to engage in innovative research and to complete the PhD within a prescribed period of study.

Applicants whose first language is not English must meet the University's English language requirements.


Applicants should email the following documents to Ms Laura Cooper; email:

  • A two-page research proposal for the selected research topic that demonstrates an understanding of the background to the area and outlines the questions that the applicant is interested in researching.
  • Curriculum vitae
  • Cover letter (one page) explaining why the candidate is interested in applying for this studentship.
  • Names and contact details of two referees

Informal enquiries about specific areas can be made to the member of staff mentioned for the topic areas above.

Candidates are not allowed to ask staff members to help in any way with the preparation of the research proposal- which must be entirely their own work

General informal enquiries can be made to Professor Ahmed Al-Dubai, or Dr Thomas Tan:

Qualification Type: PhD
Location: Edinburgh
Funding for: UK Students
Funding amount: Fully funded. The studentship will cover full UK tuition fees and will include a standard living allowance at the RCUK rate (Currently £15,609 pa).
Hours: Full Time
Placed On: 21st June 2022
Closes: 13th July 2022
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