Description

Research Associate in Computational Neuroscience

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Job number

ENG03515

Faculties

Faculty of Engineering

Departments

Department of Computing

Salary or Salary range

£48,056 - £56,345 per annum

Location/campus

South Kensington Campus - On site only

Contract type work pattern

Full time or Part time - Fixed term

Posting End Date

17 Jun 2025

About the role

The post of Research Associate (post-doctoral) will conduct research in data analysis and computational modelling of neuroimaging data, as part of a project titled “The Self, Unbound: Neurofeedback-assisted Meditation for Eliciting Transformative Self-Dissolution Experiences” in collaboration with international partners. The project seeks to build fundamental neuroscientific and computational knowledge to develop a neurofeedback system to increase well-being following continued meditation practice.

The post will be based in the Department of Computing at Imperial College London at the South Kensington Campus. The Department of Computing is a leading department of Computer Science in the UK and the world and has consistently been awarded the highest research rating. In the 2021 REF assessment, the Department claimed the top spot for computer science and informatics. In the latest QS World University Rankings, Imperial College London was recognised as the top university in Europe and the top 2 globally. Overall, Imperial College London ranked first in the UK for research outputs, first in the UK for research environment, and first for research impact among Russell Group universities.

What you would be doing

The team at Imperial College London is specifically tasked with finding the optimal biomarkers of meditative and transformative experiences, and to develop a biologically interpretable computational model that recapitulates experimental results. The candidate will undertake research both with computer simulations of brain activity and with real neuroimaging data from subjects performing meditation and in a variety of Altered States of Consciousness (ASCs). Prior experience with analysis and modelling of neural data is essential, as well as expertise in theories of complex systems applied to brain activity.

The successful candidate will collaborate with Dr Pedro Mediano in the Department of Computing, with members of Dr Mediano’s Machine Intelligence and Neural Dynamics laboratory, and with the rest of collaborators in the project.

In addition to presenting research in top computational neuroscience, complex systems, machine learning, and/or neuroimaging venues, the Research Assistant/Associate will be expected to contribute towards developing, documenting, and maintaining software and modelling tools related to this project.

Further information on the research of Dr Mediano, as well as the pre-registered study can be found at https://www.doc.ic.ac.uk/~pam213 and https://osf.io/s4rja/ respectively.

What we are looking for

• Research Associate A PhD (or be close to completion) in an area pertinent to the subject area, i.e. Computer Science, Neuroscience, Psychology, Complexity Science*.
• A proven track record of publications in top conferences or journals in the field.
• Experience in neuroimaging data analysis and modelling.
• Strong knowledge of complex systems approaches to neuroscience and of computational brain modelling techniques.
• Experience writing and publishing academic papers.

Please see job description for a full list of requirements.

*Candidates who not yet been officially awarded their PhD will be hired at Research Assistant level: salary scale £43,003 - £46,297 per annum.

What we can offer you

• The opportunity to continue your career at a world-leading institution.
• Sector-leading salary and remuneration package (including 38 days off a year).

Further information

Full time, fixed term post to start ASAP until 27th December 2026.

In addition to completing the online application candidates should attach:

• A full CV, with a list of all publications
• A 1-page research statement indicating what you see are interesting research issues relating to the above post and why your expertise is relevant.

For informal enquiries about the position please email Dr Pedro Mediano: p.mediano@imperial.ac.uk

For queries regarding the application process contact Jamie Perrins: j.perrins@imperial.ac.uk

Available documents

Attached documents are available under links. Clicking a document link will initialize its download.

• download: Research Associate in Computational Neuroscience job description Aug24 PM.pdf
• download: Employee Benefits Booklet.pdf

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Please note that job descriptions are not exhaustive, and you may be asked to take on additional duties that align with the key responsibilities mentioned above.

We reserve the right to close the advert prior to the closing date stated should we receive a high volume of applications. It is therefore advisable that you submit your application as early as possible to avoid disappointment.

If you encounter any technical issues while applying online, please don't hesitate to email us at support.jobs@imperial.ac.uk. We're here to help.

About Imperial

Welcome to Imperial, a global top ten university where scientific imagination leads to world-changing impact.

Join us and be part of something bigger. From global health to climate change, AI to business leadership, here at Imperial we navigate some of the world’s toughest challenges. Whatever your role, your contribution will have a lasting impact.

As a member of our vibrant community of 22,000 students and 8,000 staff, you’ll collaborate with passionate minds across nine London campuses and a global network.

This is your chance to help shape the future. We hope you’ll join us at Imperial College London.

Our Culture

We work towards equality of opportunity, to eliminating discrimination, and to creating an inclusive working environment for all. We encourage applications from all backgrounds, communities and industries, and are committed to employing a team that has diverse skills, experiences and abilities. You can read more about our commitment on our webpages.

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