Research Fellow in Computational Psychiatry(UK Visa Sponsorship)

Job Description

About the Role

The MPC is seeking a Research Fellow in Computational Psychiatry to join the RELMED project, a Wellcome-funded programme investigating how different antidepressant treatments engage specific reinforcement learning mechanisms.

This role will focus on the neuroimaging and electrophysiology aspects of the project. You will co-lead the EEG workstream, combining high-quality data acquisition with advanced computational modelling to understand treatment-related changes in learning and decision-making.

You will work closely with the project’s Chief Investigator, Professor Quentin Huys, who will provide academic supervision and line management. The role requires on-site working at UCL and travel to collaborating research sites when required.

Funding is secured for two years in the first instance, with the possibility of extension subject to future funding.

Key Responsibilities

Research and Project Delivery

• Co-lead the EEG component of the RELMED project
• Design, analyse, and interpret EEG experiments linked to reinforcement learning models
• Apply advanced computational and statistical modelling techniques
• Collaborate closely with clinical, computational, and experimental researchers
• Contribute to high-quality publications in peer-reviewed journals
• Collaboration and Academic Contribution
• Work effectively within a multidisciplinary research team
• Present findings at internal meetings and external conferences
• Support open, reproducible, and ethically responsible research practices
• Contribute to the intellectual life of the Centre

About You

You will hold (or be close to completing) a PhD in computational neuroscience, psychology, cognitive neuroscience, or a closely related discipline. You will bring a strong track record of high-quality research outputs and demonstrable experience conducting neuroscience research.

You will also have:

• Experience with computational and mathematical programming (e.g. MATLAB, Python, R, Java)
• Familiarity with EEG data analysis and model-based approaches
• Strong analytical, problem-solving, and communication skills
• The ability to work independently while contributing positively to a collaborative team

If the PhD has not yet been formally awarded, the appointment will initially be made at Research Assistant level, with automatic backdating to Research Fellow upon PhD submission.

Immigration and Visa Sponsorship

This role meets the eligibility criteria for sponsorship under UK Visas and Immigration regulations. UCL welcomes applications from international candidates who require visa sponsorship.

Relevant UK Government resources:

Right to work in the UK: https://www.gov.uk/check-job-applicant-right-to-work

What UCL Offers

UCL provides a supportive and competitive employment package, including:

• 41 days of leave per year (annual leave, bank holidays, and closure days)
• Option to purchase up to 5 additional days of annual leave
• Defined benefit CARE pension scheme
• Immigration loan and relocation support (where eligible)
• On-site nursery and gym facilities
• Cycle-to-work scheme and season ticket loans
• Enhanced maternity, paternity, and adoption pay
• Employee assistance and wellbeing services
• Discounted private medical insurance

Equality, Diversity and Inclusion

The Institute is committed to maintaining an inclusive, supportive, and respectful working environment where individual strengths are recognised and developed. Equality, Diversity and Inclusion (EDI) is actively embedded across Institute activities, with staff contributing to ongoing initiatives and improvements.

The Institute holds an Athena SWAN Silver Award, reflecting sustained commitment and measurable impact in advancing gender equality. UCL particularly encourages applications from candidates who are underrepresented in higher education, including individuals from Black, Asian, and minority ethnic backgrounds; disabled people; LGBTQI+ and gender-diverse people; and women in senior roles.

How to Apply

To apply, please submit:

• A current CV
• A supporting statement or cover letter explaining how you meet the essential and desirable criteria

Please do not upload additional documents, as these will not be reviewed.