Postdoctoral Research Associate

Working at Durham University  

A globally outstanding centre of teaching and research excellence, a warm and friendly place to work, a unique and historic setting – Durham is a university like no other.

As one of the UK’s leading universities, Durham is an incredible place to define your career.The University is located within a beautiful historic city, home to a UNESCO World Heritage Site, and surrounded by stunning countryside. Our talented scholars and researchers from around the world are tackling global issues and making a difference to people's lives.  

We believe that inspiring our people to do outstanding things at Durham enables Durham people to do outstanding things in the world. Being a part of Durham is about more than just the success of the University, it’s also about contributing to the success of the city, county and community.

Our University Strategy is built on three pillars of research, education and wider student experience, but also on our keen sense of community and of inspiring others to achieve their potential. 

Our Purpose and Values

We want our University to be a place where people can be free to be themselves, no matter what their identity or background. Together, we celebrate difference, value one another and are each responsible for creating an inclusive community that is respectful and fair for all.

Find out more about the benefits of working at the University and what it is like to live and work in the Durham area on our  Why Join Us? - Information Page

The Role and Department

The Department of Computer Science at Durham University is one of the UK’s leading centres for computer science education and research, consistently ranked in the national top 10 (Complete University Guide 2025) and 4th for graduate prospects in 2026. We are a fast-growing department, expanding from 30 to 50 academic staff in recent years with plans to grow further, and are based in a new purpose-built facility on the Upper Mountjoy Campus, designed to support collaboration, innovation and interdisciplinary working. Our research has been recognised as internationally excellent and world-leading in REF 2021, and we ranked 3rd in the UK for interdisciplinary science research in the Times Higher Education Interdisciplinary Rankings 2025. Situated in the historic and vibrant city of Durham, the department offers an ambitious, supportive and forward-looking environment in which colleagues can develop their careers and contribute to shaping the future of computer 

The Role

The role focuses on advancing research in explainable and trustworthy machine learning, with a particular emphasis on mechanistic interpretability and its application to healthcare data. The successful candidate will contribute to understanding how modern machine learning models represent information internally and how their predictions can be made transparent, reliable, and clinically meaningful. This work will involve developing and applying interpretability techniques to machine learning systems used in healthcare contexts, including tasks such as risk prediction, clinical decision support, and the analysis of complex biomedical datasets. The research environment is highly interdisciplinary, bringing together expertise from machine learning, statistics, data science, and healthcare research.

The successful applicant will be expected to design and implement analytical and interpretability frameworks to investigate the internal representations and decision-making processes of machine learning models. This includes developing and applying techniques such as feature attribution, representation analysis, causal probing, and mechanistic circuit analysis. The postholder will also develop predictive models using modern deep learning frameworks (e.g., PyTorch) and evaluate them with a focus on interpretability, robustness, and real-world applicability in healthcare settings.

The role also involves developing reproducible research software and scalable data analysis pipelines in Python for machine learning and interpretability research. These tools will support systematic investigation of model behaviour and enable robust experimentation on large and complex datasets relevant to healthcare and biomedical research.

The postholder will be expected to contribute actively to high-quality research outputs, including peer-reviewed publications in leading machine learning and interdisciplinary venues, open-source software tools, and collaborative research initiatives. The successful candidate will also contribute to the preparation and development of research grant proposals, supporting the group’s strong track record of successful funding and helping to expand its research portfolio in explainable and trustworthy AI for healthcare.

Key responsibilities:

• To understand and convey material of a specialist or highly technical nature in machine learning interpretability and explainable AI to the research team and collaborators through presentations and discussions that contribute to the preparation of research papers, conference presentations, and grant proposals.
• To prepare and deliver presentations on research outputs and activities to audiences which may include research sponsors, academic collaborators, healthcare researchers, and interdisciplinary audiences.
• To publish high-quality research outputs, including papers for submission to peer-reviewed journals and papers for presentation at conferences and workshops, under the direction of the Principal Investigator or Grant-holder.
• To assist with the development of research objectives, pilot studies, and grant proposals focused on mechanistic interpretability and explainable AI methods for healthcare applications.
• To conduct individual and collaborative research in explainable AI and mechanistic interpretability, including the development of proof-of-concept models, interpretability methods, and analytical frameworks under the direction of the Principal Investigator or Grant-holder.
• To develop prototype machine learning models and interpretability pipelines (e.g., using PyTorch and Python-based data analysis tools) to explore how model representations and decision mechanisms can be understood and evaluated in healthcare contexts.
• To work with the Principal Investigator or Grant-holder and other colleagues in the research group, as appropriate, to identify emerging research opportunities, develop novel methodological approaches, and extend the group’s research portfolio in explainable and trustworthy AI.
• To address challenges that may affect the achievement of research objectives and timelines by discussing issues with the Principal Investigator or Grant-holder and proposing creative or innovative solutions.
• To liaise with research colleagues and establish internal and external contacts to develop knowledge and understanding and build relationships that may lead to future collaborative research and funding opportunities.
• To plan and manage personal research activities and resources, in collaboration with others, and contribute to the planning and coordination of research activities associated with pilot studies and grant development.
• To contribute to the development of research software and reproducible analysis pipelines that support experimentation, interpretability analysis, and data-driven healthcare research.
• To deliver training in research techniques and approaches to peers, visitors, and students as appropriate, particularly in areas related to machine learning, interpretability methods, and reproducible research practices.
• To be involved in student supervision, as appropriate, and assist with the assessment of the knowledge of students where relevant.
• To contribute to fostering a collegial and respectful working environment that is inclusive and welcoming, and where everyone is treated fairly with dignity and respect.
• To engage in wider citizenship to support the department and the wider research community.
• To engage in continuing professional development by participating in relevant training and development activities, including seminars, workshops, and collaborative research initiatives.
• To undertake any other duties that are commensurate with the nature of the role and contribute to the development of a future programme of research in explainable and interpretable AI for healthcare.

This post is fixed-term for 9 months starting on the 27th March 2026 and ending on the 31st December 2026. The appointment is intended to support the development of proof-of-concept research in mechanistic interpretability and explainable AI for healthcare, including the development of preliminary models, interpretability analyses, and prototype research software. The outputs from this work will form the basis of peer-reviewed publications and competitive grant applications aimed at securing longer-term funding for a larger research programme in trustworthy and interpretable AI in healthcare.

The post-holder is employed to work on research/a research project which will be led by another colleague. Whilst this means that the post-holder will not be carrying out independent research in his/her own right, the expectation is that they will contribute to the advancement of the project, through the development of their own research ideas/adaptation and development of research protocols.

Successful applicants will, ideally, be in post by 27th March 2026

Working at Durham 

A competitive salary is only one part of the many fantastic benefits you will receive if you join the University:

• You’ll receive 30 days annual leave per year in addition to 8 public holidays and 4 customary days per year – a total of 42 days per year. The University closes between Christmas and New Year.

• We offer a generous pension scheme, and as a new member of staff you will be automatically enrolled into the University Superannuation Scheme (USS).

• No matter how you travel to work, we have you covered.  We have ample parking across campus, a cycle to work scheme which helps you to buy a bike and discount with local bus and train companies. You can also take advantage of our cost-effective and environmentally friendly Tusker Car Benefit Scheme, allowing you to lease a brand-new electric or hybrid vehicle with savings on tax and National Insurance.

• We have a genuine commitment to developing our colleagues professionally and personally.  There is a comprehensive range of development courses, apprenticeships and access to qualifications and routes to develop your career in the University.  All staff have dedicated annual time to concentrate on their personal development opportunities.

• We provide wide-ranging health and wellbeing support including discounted membership for our state-of-the-art sport and gym facilities and access to a 24-7 Employee Assistance Programme.

• Our on-site nursery is rated Outstanding by Ofsted, and you can access holiday camps for children aged 5-16.

• Our family-friendly policies, including maternity and adoption leave, are among the most generous in the higher education sector (and likely above and beyond many employers).

• We offer all staff the opportunity to take part in volunteering activities to make a difference in the local community.

• You can access exclusive discounts via our benefits portal including money off at supermarkets, high street retailers, IT products such as Apple, eating out and days out at various attractions.

• Various salary sacrifice schemes are also available to help you take advantage of tax savings on benefits.

• If you are moving to Durham, you may be eligible for help with removal costs, and we have a dedicated team who can help you with the practicalities such as house hunting and schools.  If you need a visa, we cover most visa costs and offer an interest-free loan scheme to pay for dependant visas.

Discover more about our total rewards and benefits package here .

Durham University is committed to equality, diversity and inclusion

Equality, diversity, and inclusion (EDI) are a key component of the University’s Strategy and a central part of everything we do.  We also live by our Purpose and Values  and our Staff Code of Conduct.   At Durham we actively work towards providing an environment where our staff and students can study, work and live in a community which is supportive and inclusive.

We welcome and encourage applications from those who are currently under-represented in our work force, including people with disabilities and from racially minoritised ethnic groups.

If you have taken a career break or periods of leave that may have impacted on the volume and recency of your research outputs and other activities, such as maternity, adoption or parental leave, you may wish to disclose this in your application. The selection committee will take this into account when evaluating your application.

The University has been awarded the Disability Confident Leader status. If you are a candidate with a disability, we are committed to ensuring fair treatment throughout the recruitment process. We will make adjustments to support the interview process wherever it is reasonable to do so and, where successful, reasonable adjustments will be made to support people within their role. 

Contact Information 

Department contact for academic-related enquiries 

PROFESSOR NOURA AL MOUBAYED  noura.al-moubayed@durham.ac.uk

Contact information for technical difficulties when submitting your application 

If you encounter technical difficulties when using the online application form, we prefer you send enquiries by email.  Please send your name along with a brief description of the problem you’re experiencing to e.recruitment@durham.ac.uk  

Alternatively, you may call 0191 334 6801 from the UK, or +44 191 334 6801 from outside the UK. This number operates during the hours of 09.00 and 17.00 Monday to Friday, UK time.  We will normally respond within one working day (Monday to Friday, excluding UK public holidays).  

University contact for general queries about the recruitment process 

How to Apply  

To progress to the assessment stage, candidates must evidence each of the essential criteria required for the role in the person specification below. It will be at the discretion of the recruiting panel as to whether they will also consider any desirable criteria, but we would urge candidates to provide evidence for all criteria.  

While some criteria will be considered at the shortlisting stage, other criteria may be considered later in the assessment process, such as questions at interview.  

Submitting your application 

We prefer to receive applications online.   We will update you about your application at various points throughout the selection process, via automated emails from our e-recruitment system. Please check your spam/junk folder periodically to make sure you have not missed any of our updates.

What to Submit 

All applicants are asked to submit: 

• a CV and cover letter which details your experience, skills, and achievements in meeting (or the potential to meet) the criteria set out below.

   

Next Steps 

  Short-listed candidates will be invited to the University, either virtually or in-person and will have the opportunity to meet key members of t       the Department. The assessment for the post will normally include a presentation to the panel and we anticipate that the assessments                       and interviews will take place over one day in or around ASAP.

In the event that you are unable to attend in person on the date offered, it may not be possible to offer you an interview on an alternative date. 

Please note that in submitting your application Durham University will be processing your data. We would ask you to consider the relevant University Privacy Statement  Job Applicants/Potential Job Applicants - Durham University which provides information on the collation, storing and use of data.   

When appointing to this role the University must ensure that it meets any applicable immigration requirements, including salary thresholds which are applicable to some visas.

Person Specification

Essential Criteria:

1. Qualifications

• A good first degree in Computer Science, Artificial Intelligence, Data Science or a closely related discipline.
• A PhD in Explainable Artificial Intelligence, Machine Learning, or a closely related field, with clear relevance to explainable AI for healthcare applications.

2. Experience

• Postdoctoral research experience in explainable AI, machine learning, or a closely related field.
• Experience in conducting high-quality academic research in explainable AI, mechanistic interpretability, or interpretable machine learning, ideally with applications to healthcare or biomedical data.
• Demonstrable experience in machine learning and explainable AI methods, including the development or analysis of interpretable models.
• Proven track record of high-quality publications, including papers in leading peer-reviewed journals and/or top-tier conferences, commensurate with stage of career.
• Demonstrable experience in attracting or contributing to successful research funding, including participation in grant applications or funded research projects.
• Demonstrable ability to write material of a quality commensurate with publication in highly ranked journals and leading conferences.
• Demonstrable ability to present research papers at national and international conferences and communicate complex information to specialist and interdisciplinary audiences.

3. Skills

• Demonstrable ability to work cooperatively as part of a research team, including participating actively in research meetings and collaborative projects.
• Ability to work independently on own initiative and deliver research outputs to strict deadlines.
• Excellent interpersonal, communication and presentation skills.

Desirable:

4. Experience

• Experience applying explainable AI or interpretable machine learning techniques to healthcare or biomedical datasets.
• Experience developing or applying mechanistic interpretability or advanced model interpretability methodsfor modern machine learning systems.
• A strong publication record in peer-reviewed journals and leading conferences in AI or machine learning, commensurate with stage of career.
• Demonstrable ability to develop research proposals and grant applications in collaboration with academic partners.
• Experience supervising or mentoring students with respect to the development of their practical or research skills (e.g., supervising student projects or acting as a demonstrator).
• Experience collaborating in interdisciplinary research environments, particularly those involving healthcare or biomedical research.

5. Skills

• Demonstrable ability to plan and manage independent research and contribute to the development of new research directions.
• Demonstrable ability to work effectively in collaborative teams and support the development of a positive and productive research environment.