Postdoctoral Research Associate in Machine Learning

Institute for Medical Humanities, Durham University; North East; On-site; GBP 38,000 - 46,000; Full time

Job description

Postdoctoral Research Associate in Machine Learning (

Job Number:

25000466)

Department of Computer Science

Grade 7: - £38,249 - £45,413 per annum

Fixed Term - Full Time

Contract Duration: 24 months

Contracted Hours per Week: 35

Closing Date

: 14-May-2025, 10:59:00 PM

Disclosure and Barring Service Requirement: Not Applicable.

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.

The Department

Computer Science at Durham is a UK Top 10 Department (Complete University Guide 2024). We are committed to high-quality teaching and research, and the Department increased excellence in all research areas since the last research assessment exercise, moving six places up the ranking to the 20th position for REF 2021. We are proud of our emphasis on equality, diversity and inclusion and are working hard to make our department the No. 1 University in the UK for women to study Computer Science.

The Role

The successful applicant will be responsible for the design, development, and implementation of deep learning and computer vision frameworks across a range of research projects. This includes developing and training deep learning models for tasks such as scene understanding, object detection, segmentation, classification, and pose estimation, as well as integrating these models into real-time systems. The role will involve working with large and multi-modal datasets (e.g., images, video, audio, and sensor data), and deploying solutions in real-world environments, particularly in robotics-focused applications. Familiarity with robotics concepts such as SLAM, sensor fusion, visual odometry and hardware integration is highly desirable. The candidate will be expected to contribute to experimental design, evaluation using benchmark datasets, and the development of reproducible and scalable solutions. A flexible and creative approach to problem-solving is essential, as projects may span a range of domains including environmental monitoring, autonomous navigation and intelligent perception systems.

Collaboration with our European partners is anticipated, and the successful candidate will be encouraged to adopt a creative approach to problem-solving, exploring various deep learning techniques. Verification of these models and algorithms will be conducted using benchmark datasets and real-world tests in diverse aquatic environments, necessitating a willingness to engage in experimental work for real-world verification with biologists and other stakeholders. This role will involve close collaboration with external partners across EU. You will be expected to visit several of partner institutions in the course of your work and will be based in the Department of Computer Science at Durham University.

Key Responsibilities:

• To conduct individual and collaborative research projects under the direction of the line manager.
• To design and develop novel and cutting-edge machine learning, computer vision and image processing frameworks for tasks such as object detection, segmentation, pose estimation, scene understanding and multi-modal perception.
• To contribute to the development and integration of AI models in real-world systems, including robotic applications involving SLAM, autonomous navigation, sensor fusion, and visual-inertial odometry.
• To explore the application of foundation models, including large vision-language models (VLMs) and large language models (LLMs), in enhancing perception, reasoning and decision-making capabilities.
• To understand and convey material of a specialist or highly technical nature to the team or group of people through presentations and discussions that leads to the presentation of research papers in conferences and publications.
• To prepare and deliver presentations on research outputs/activities to audiences which may include: research sponsors, academic and non-academic audiences.
• To publish high quality 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 and proposals.
• To work with the line manager and other colleagues in the research group, as appropriate, to identify areas for research, develop new research methods and extend the research portfolio.
• To deal with problems that may affect the achievement of research objectives and deadlines by discussing with the Principal Investigator or Grant-holder and offering creative or innovative solutions.
• To liaise with research colleagues and make internal and external contacts to develop knowledge and understanding to form relationships for future research collaboration.
• To plan and manage own research activity, research resources in collaboration with others and contribute to the planning of research projects.
• To deliver training in research techniques/approaches to peers, visitors and students as appropriate.
• To be involved in student supervision, as appropriate, and assist with the assessment of the knowledge of students.
• To contribute to fostering a collegial and respectful working environment which is inclusive and welcoming and where everyone is treated fairly with dignity and respect.
• To engage in wider citizenship to support the department and wider discipline.
• To engage in continuing professional development by participation in the undergraduate or postgraduate teaching programmes or by membership of departmental committees, etc. and by attending relevant training and development courses.
  
  

This post is fixed term for 24 months due to the project's available funding.

The post-holder is employed to work on research 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 June 2025.

Working at Durham

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

• 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, 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 parking across campus, a cycle to work scheme which helps you to buy a bike and discount with local bus and train companies.
• There is 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.
• Lots of support for health and wellbeing including discounted membership for our state of the art sport and gym facilities and access to a 24-7 Employee Assistance Programme.
• On site nursery is available plus access to holiday camps for children aged 5-16.
• Family friendly policies, including maternity and adoption leave, which are among the most generous in the higher education sector (and likely above and beyond many employers).
• The opportunity to take part in staff volunteering activities to make a difference in the local community
• Discounts are available via our benefits portal including; money off at supermarkets, high street retailers, IT products such as Apple, the cinema and days out at various attractions.
• A salary sacrifice scheme is 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.
  
  

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. It’s important to us that all colleagues undertake activities that are aligned to both our values and commitment to EDI.

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

For informal enquiries please contact Dr Amir Atapour-Abarghouei ([e-mail]). All enquiries will be treated in the strictest confidence.

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-mail]

Alternatively, you may call 0191 334 6801 from the UK, or [phone] 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

[e-mail]

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 (maximum 4 pages) and a 1-page cover letter which details your experience, strengths and potential in 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 the Department. The assessment for the post will normally include a formal interview and a technical interview. and we anticipate that the assessments and interviews will take place over two days in or around May 2025.

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.

Qualifications

Person Specification Essential Criteria:

• A good first degree in Computer Science, Machine Learning, Maths and Statistics, Robotics or a related subject.
• A PhD (or an MSc with extensive research experience) in Computer Science, Machine Learning, Maths and Statistics or a related subject.
  
  

Experience

• Strong experience in conducting high quality academic research in deep learning, machine learning, computer vision and multi-modal data processing for real-world robotic applications.
• Strong background in deep learning, supervised and unsupervised learning, time-series analysis, information visualisation, with experience in developing and implementing very large deep learning models.
• Familiarity with high performance computing environments (e.g., HPC clusters, GPUs, Cloud resources) and managing Linux based hardware systems.
• Strong experience in programming for model development and designing experimental environments for deep learning applications using PyTorch, TensorFlow, JAX, etc.
• Demonstrable experience in data processing and analysis using state-of-the-art data science languages (e.g., Python) as well as experience in programming languages such as Python, C and C++.
  
  

Skills

• Demonstrable ability to present research papers at conferences and communicate complex information to specialists and within the wider academic community.
• Demonstrable ability to write material of a quality commensurate with publication in highly-ranked journals, evidenced by publication record.
• Ability to work independently on own initiative and to strict deadlines.
• Excellent interpersonal and communication skills.
  
  

Desirable Criteria

Experience

• Experience of working in a multidisciplinary team.
• Previous experience with deep learning and computer vision techniques applied to robotics, biological or ecological research, or environmental monitoring; including tasks such as object detection, segmentation and classification in complex, real-world settings.
• Familiarity with additional areas such as SLAM, 3D reconstruction, multi-modal data fusion and neuromorphic sensing or processing. A demonstrated ability to adapt AI techniques across domains and integrate them into real-time or embedded systems is highly desirable.
  
  

Other

• Willingness to travel.