Postdoctoral Research Associate in Machine Learning

Working at Durham University

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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.

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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 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

TheBioDiMoBotproject will deliver a system for autonomous, long-term robotic assessments of aquatic biodiversity and ecology. This project will develop an innovative measurement system to monitor biodiversity and provide insight into the drivers of ecosystem degradation. Additionally, it will assess organismic and environmental stress levels by using novel biohybrid sensors. With the BioDiMoBots' ability to perform autonomous and automated multimodal long-term data collection, the project will create a user-friendly robotic tool that provides detailed insights into the ecological health of aquatic environments. The project will be driven by the needs of potential stakeholders such as researchers, small and medium-sized enterprises in water-related industries and policy-makers. Field operations will demonstrate the transformative power of the BioDiMoBot systems by monitoring aquatic ecosystems over a long period of time.

The successful applicant will be responsible for the design, development, and implementation ofdeep learning,computer vision,image processinganddata analysisframeworks for the BioDiMoBot system as well as somelower-level programmingfor the user interface and robotic integration. The primary tasks will includedeveloping and training large deep learning modelsfor automated species identification and environmental stress assessment, as well as integrating these models into the robotic system. Additionally, the role involves processing and analysing large datasets of images andunderwater soundsand deploying AI solutions for real-time data collection and interpretation.

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.

The project is a HORIZON funded collaboration between the University of Durham in the UK, the University of Graz in Austria, Universite Libre de Bruxelles in Belgium, Scuola Superiore Sant'Anna in Italy, SYRION in Austria, Oesterreichische Bundesforste in Austria and Carbon Kapture (Mulroy Bay) Ltd in the UK. This role will involve close collaboration with these external partners. You will be expected to visit several of these 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 Principal Investigator or Grant-holder.
• To design and develop novel and cutting-edge deep learning and image processing frameworks for automated species identification and environmental stress assessment, as well as frameworks needed for other, similar research.
• 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 line manager.
• 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 line manager 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/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 byJanuary 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.

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. 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 Employer 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

Dr Amir Atapour-Abarghouei,

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 abrief description of the problem you're experiencing

Alternatively, you may call from the UK, or 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

If you have any queries about the recruitment process, please contact the recruitment team on .

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 (maximum4 pages) and a1-pagecover letter which details your experience, skills, and achievements in meeting (or the potential to meet) the criteria set out below.

Next Steps

The assessment for the post will include aformal interviewand atechnical interview. Shortlisted candidates will be invited for interview in September/October 2024.

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:

Qualifications

1. A good first degree in Computer Science, Machine Learning, Maths and Statistics, Robotics or a related subject.

2. A PhD (or be close to submission) in Computer Science, Machine Learning, Maths and Statistics, Robotics, or a related subject.

Experience

3. 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.

4. 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.

5. Familiarity with high performance computing environments (e.g., HPC clusters, GPUs, Cloud resources) and managing Linux based hardware systems.

6. Strong experience in programming for model development and designing experimental environments for deep learning applications using PyTorch, TensorFlow, JAX, etc.

7. Demonstrable experience in data processing and analysis using in state-of-the-art data science languages (e.g., Python, R) as well as experience in programming languages such as Python, C and C++.

Skills

8. Demonstrable ability to present research papers at conferences and communicate complex information to specialists and within the wider academic community.

9. Demonstrable ability to work cooperatively as part of a team, including participating in research meetings.

10. Ability to work independently on own initiative and to strict deadlines.

11. Excellent interpersonal and communication skills.

Desirable Criteria

Experience

12. Experience of working in a multidisciplinary team.

13. Previous experience with deep learning and computer vision techniques for biological or ecological research or environmental monitoring.

Other

14. Willingness to travel.