Research Fellow in London

You should have a PhD (or be near completion) in a relevant discipline (e.g., psychology, neuroscience, neurodegeneration or related discipline) and experience in quantitative analysis of neuroimaging data. Experience in quantitative research methods, programming and statistical modelling with the ability to plan and execute rigorous statistical models and good understanding of research ethics are essential as is evidence of scholarly productivity, and experience of analysing neuroimaging data. Excellent coding skills, and prior experience in imaging analysis within neurodegeneration (particularly in people with Parkinson's disease and those treated with deep brain stimulation) are desirable.

This role meets the eligibility requirements for a skilled worker certificate of sponsorship or a global talent visa under UK Visas and Immigration legislation. Therefore, UCL welcomes applications from international applicants who require a visa.

The Institute prides itself on operating in an all-inclusive environment irrespective of personal, physical, or social characteristics. Teamwork is highly valued, individual strengths are recognised and celebrated, and we are committed to advancing the careers of everyone. 12% of Institute staff are actively working on Equality, Diversity and Inclusion (EDI) initiatives; visit our EDI website for more information about our initiatives and priorities. The Institute also holds an Athena SWAN Gold award, in recognition of our commitment and demonstrable impact in advancing gender equality.

As London's Global University, we know diversity fosters creativity and innovation, and we want our community to represent the diversity of the world's talent. We are committed to equality of opportunity, to being fair and inclusive, and to being a place where we all belong.

We therefore particularly encourage applications from candidates who are likely to be underrepresented in UCL's workforce; these include people from Black, Asian and ethnic minority backgrounds, disabled people, LGBTQI+ and gender diverse people in all roles, and women in Grade 9 and 10 roles.

We are seeking a Research Fellow to help advance a research programme on developing neuroimaging-informed non-invasive stimulation approaches.

You will integrate structural, functional and neurochemical imaging measures to identify brain circuits associated with cognitive decline and help define targets for focused ultrasound stimulation. You will also contribute to the delivery and evaluation of ultrasound stimulation studies, the interpretation and dissemination of findings, and the development of new analytical approaches and research questions across the programme.

You will be expected to make an intellectual contribution to Parkinson's dementia, as well as possess the technical skills to complete functional and structural analysis of large brain imaging data sets. You should aspire to being an academic researcher and are expected to be present at and attend conferences, supervise doctoral, master's and bachelor's students, assist with teaching when on offer, interact with funders, publish manuscripts, and conduct high-quality scientific research.

The post is available from 11 January 2027 and is funded by UKRI for one year in the first instance.

This role is eligible for hybrid working with a minimum of 80% of time on site.

If you need reasonable adjustments or a more accessible format to apply for this job online, or have any queries regarding the application process, please contact the Institute of Neurology HR Team (ion.hradmin@ucl.ac.uk).

For informal enquiries about the role please contact Dr Angelika Zarkali (email: a.zarkali@ucl.ac.uk).

We expect to hold interviews on 02 December 2026.

A full job description and person specification for this role can be accessed below. To apply, please upload a current CV, complete the online application form, and use the supporting statement section or upload a cover letter to outline how you meet the essential and desirable criteria for the role. Please do not upload any additional attachments as these will not be considered by the selection panel.