Research Fellow in Applied AI for the Energy Transition

Applications are invited for the position of Research Fellow in Applied AI for the Energy Transition within the James Watt School of Engineering.

This position offers a unique opportunity to contribute to a major new UKRI-funded Fellowship at the intersection of artificial intelligence, scientific machine learning and subsurface engineering. The research focuses on developing physics-informed machine learning approaches to improve understanding of the subsurface, a critical challenge in the deployment of offshore wind and other net-zero energy infrastructure.

Prior domain experience in geotechnics, geophysics or offshore engineering is not required. We welcome applications from candidates in machine learning, artificial intelligence, computer science, statistics, data science, engineering, applied mathematics, physics or a closely related discipline.

The successful candidate will undertake research in physics-informed machine learning, uncertainty quantification, predictive modelling and geospatial data integration to improve subsurface characterisation and support decision-making for offshore renewable energy developments. The research will create opportunities for methodological advances in machine learning and uncertainty-aware modelling while addressing important challenges in offshore renewable energy and the net-zero transition.

The postholder will join an interdisciplinary team of engineers, data scientists and geophysicists led by Dr Róisín Buckley as part of a UKRI-funded Fellowship. The role offers opportunities to collaborate with leading academic and industrial partners, including researchers across the UK's AI ecosystem in data science and artificial intelligence. The successful candidate will have access to world-class experimental and computational facilities and will play a key role in shaping an ambitious research programme at the interface of geophysics, engineering and AI.

Main Duties and Responsibilities:

1. Play a leading role in the management and development of the project and to work independently and in collaboration to bring the project to a successful completion including establishing and maintaining external collaborations both nationally and internationally.
2. Play a leading role in the planning, design and conduct of research, individually or jointly, in accordance with the project deliverables and project/Institute/College/University research strategy.
3. Establish and maintain an extensive research profile and reputation, sustaining a track record of independent and joint publications of international quality in high profile/quality refereed publications, enhancing the research impact in terms of economic/societal benefit, and gathering indicators of esteem.
4. Play a leading role in the presentation of research findings at high profile national and international conferences, seminars and meetings to enhance the research profile of the project/Institute/College/University.
5. Lead the development, both independently and in collaboration with others (including stakeholders), of the identification of potential funding sources and lead in the development of proposals to secure funding from internal and external bodies to support future research of international quality.
6. Take a leading role in developing and maintaining collaborations with colleagues across the project and in the broader Institute/College/University and wider community.
7. Play a leading role in the organisation, supervision, mentoring and training of undergraduate and/or postgraduate students and less experienced members of the project team to ensure their effective development.
8. Perform administrative tasks related to the activities of the research group and School, including budgets/expenditure.
9. Supervise Masters students and act as co-supervisor to PhD students as assigned by the Director of Institute and/or senior group leader.
10. Keep up to date with current knowledge and recent advances in the field/discipline in order to provide advice and guidance to students and less experienced colleagues.
11. Engage in personal, professional and career development, to enhance both specialist and transferable skills in accordance with desired career trajectory.
12. Undertake any other reasonable duties as required by the Head of School/Director of Research Institute.
13. Contribute to the enhancement of the University's international profile in line with the University Strategy.

Knowledge/Qualifications:

Essential:
- Normally Scottish Credit and Qualification Framework level 12 (PhD) in machine learning, artificial intelligence, computer science, statistics, data science, engineering, applied mathematics, physics or a closely related discipline, plus track record of emerging independence within a research/professional environment, or alternatively possess professional qualifications and experience equivalent to PhD level plus the requisite experience.
- A comprehensive and up-to-date knowledge of current issues and future directions within the wider subject area or subject specialism.
- Specialist theoretical and practical knowledge of research methods, technical models, and techniques relevant to the project/discipline.

Skills:

Essential:
- Excellent scientific programming skills, and experience with modern machine-learning frameworks.
- An established track record of presentation and publication of research results in quality publications.
- Commitment to open research through open data, open code, open educational resources and practices that support replication.
- Proven commitment to supporting career development of colleagues and to other forms of collegiality appropriate to the career stage.

Experience:

Essential:
- Experience developing and applying machine-learning methods to scientific, engineering, environmental, geospatial, or physical-system datasets.
- Experience of delivering quality outputs in a timely and efficient manner.
- Experience of independence as illustrated by identification of project objectives from assessment of literature, design and analysis of research data and drafting of papers.
- Sufficient depth of relevant research experience in a relevant or related field, appropriate to an early career researcher.

Desirable:
- Experience managing, processing and analysing large and complex datasets, including development of reproducible computational workflows.
- Experience working within interdisciplinary research teams spanning computational and domain sciences.
- Experience of participating in activities that translate research into impact to benefit the economy and wider society.
- Experience of contributing to the design and delivery of teaching and assessment in higher education or other relevant environments.

Terms and Conditions:

This post is full time (35 hours per week) and has funding available until 30 September 2029 in the first instance. All applicants must have the right to live and work in the UK or be eligible to obtain permission to work in the UK. This role may be eligible for sponsorship under the Skilled Worker visa route or the Global Talent visa route, subject to meeting the relevant Home Office requirements.

Benefits include: a warm welcoming and engaging organisational culture; an excellent employment package with 41 days of leave for full time staff, pension, benefits and discount packages; a flexible approach to working; and a commitment to support health and wellbeing, including a free 6-month UofG Sport membership for all new staff.