AI Research Specialist

Research Track

COLLEGE OF MVLS

GRADE 7

Background

Job Purpose

To develop, test, and implement AI/Machine Learning models for the analysis of real-world healthcare applications using NHS data hosted within the Trusted Research Environment (TRE).  The postholder will play a key role in supporting collaborative, translational research between NHS Greater Glasgow and Clyde (NHSGGC) and the University of Glasgow (UofG), ensuring rigorous statistical integrity, ethical compliance and translational innovation to improve patient outcomes and support academic excellence.

Main Duties and Responsibilities

1.      Design, build, and validate AI/machine learning models to analyse complex clinical datasets hosted in the TRE to support principal investigators of projects.

2.      Develop foundational AI workflows and pipelines, ensuring reproducibility, transparency, and ethical integrity.

3.      Working closely with clinicians, researchers, and data engineers across NHS and UofG to identify impactful use cases and translate needs into deployable AI solutions.

4.      To work independently and lead on technical aspects of model training, hyperparameter optimisation, validation, interpretability, and deployment within a secure TRE environment.

5.      Ensure all research activities comply with NHS data governance, ISO standards, and the TRE’s ethical frameworks.

6.      Contribute to demonstration projects (e.g., digital pathology, imaging foundation models, and text-based NLP) that showcase the TRE’s AI/ML capabilities.

7.      Act as a technical liaison across the NHS Safe Haven, academic researchers, and University Services (e.g., Information Services, Centre for Data Science and AI) advising on appropriate study designs, advanced modelling techniques.

8.      Support the training and mentoring of junior researchers and students in AI methodologies and TRE usage.

9.      Perform administrative tasks related to the activities of the research group, including Budgeting, and any other administrative tasks relevant to research governance.

10.   Keep up to date with current knowledge and recent advances in the field / discipline.

11.   Contribute to research publications, grant applications, and dissemination activities to secure external funding and enhance the University’s research profile.

12.   Participate and engage with national and cross-institutional AI/TRE initiatives and networks as appropriate.

13.   Undertake any other reasonable duties as required by the Head of School / Director of Clinical TRE

14.   Contribute to the enhancement of the University’s international profile in line with the University Strategy.

Qualification, Knowledge, skills and experience

Qualifications/Knowledge

Essential:

A1 Scottish Credit and Qualification Framework level 12 (PhD) or alternatively possess the equivalent in professional qualifications and experience, with experience of personal development in a similar or related role(s) within a relevant discipline such as Computer Science, Health Informatics, Data Science Biomedical Engineering or similar related field.

A2 Good knowledge of machine learning and AI principles, particularly in applied healthcare contexts.

A3 Demonstrable understanding of data governance and regulatory requirements for clinical data, including anonymisation and secure data handling protocols.

A4 Basic knowledge and familiarity with the principles and practices underpinning Trusted Research Environments (TREs).

Skills

Essential:

C1 Proficiency in programming languages such as Python or R, and experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).

C2 Ability to manipulate and analyse large, complex datasets using secure computing platforms.

C3 Excellent communication and interpersonal skills to work across interdisciplinary teams in both academic and clinical environments.

C4 Proven ability to explain complex technical concepts to non-specialist stakeholders, including clinicians and policymakers.

C5 Problem-solving mindset with the ability to work independently and manage multiple priorities.

Experience

Essential:

E1 Significant experience in developing, evaluating, and deploying machine learning models in research or industry settings.

E2 Experience working with sensitive health or clinical datasets within secure research environments or safe havens.

E3 Strong track record of interdisciplinary collaboration, preferably involving both academic and healthcare stakeholders.

E4 Experience contributing to peer-reviewed publications or grant-funded research projects.

E5 Experience working within data governance and ethical frameworks, ideally in healthcare or public sector research.

E6 Proven commitment to supporting the career development of colleagues and to other forms of collegiality appropriate to the career stage

Terms and Conditions

Salary will be Grade 7, £40,497 - £45,413 per annum.

This post is full time (35 hours p/w) and open ended. Relocation assistance will be provided where appropriate.

As a valued member of our team, you can expect:

1 A warm welcoming and engaging organisational culture, where your talents are developed and nurtured, and success is celebrated and shared.

2 An excellent employment package with generous terms and conditions including 41 days of leave for full time staff, pension - pensions handbook https://www.gla.ac.uk/myglasgow/payandpensions/pensions/, benefits and discount packages.

3 A flexible approach to working.

4 A commitment to support your health and wellbeing, including a free 6-month UofG Sport membership for all new staff joining the University  https://www.gla.ac.uk/myglasgow/staff/healthwellbeing/.

We believe that we can only reach our full potential through the talents of all. Equality, diversity and inclusion are at the heart of our values. Applications are particularly welcome from across our communities and in particular people from the Black, Asian and Minority Ethnic (BAME) community, and other protected characteristics who are under-represented within the University. Read more on how the University promotes and embeds all aspects of equality and diversity within our community https://www.gla.ac.uk/myglasgow/humanresources/equalitydiversity/.

We endorse the principles of Athena Swan https://www.gla.ac.uk/myglasgow/humanresources/equalitydiversity/athenaswan/ and hold bronze, silver and gold awards across the University.

We are investing in our organisation, and we will invest in you too. Please visit our website https://www.gla.ac.uk/explore/jobs/ for more information.

Closing Date: 21 July 2025 at 23:45