Job Description

The Digital Mental Health Group is an innovative and collaborative research group studying the intersection between digital technologies, adolescent mental health and developmental cognitive neuroscience, with the aim of improving mental health outcomes in both non-clinical and clinical populations. We are based at the MRC Cognition and Brain Sciences Unit, University of Cambridge, a world-leading research centre well-known for its close-knit community, friendly atmosphere, and outstanding research support.


We are seeking a post-doctoral research associate with experience in computational approaches (e.g., Reinforcement Learning, Agent Based Modelling) to join our team full-time as part of a large international collaboration of European researchers (incl. Tobias Dienlin, Veronica Kalmus, Adrian Meier, Charo Sadaba). You will be responsible for completing research projects fitting computational models to social media behavioural data (e.g., see https://doi.org/10.1038/s41467-020-19607-x). This data will be collected observationally and as part of experiments where the social media interface participants are using is manipulated. You will be expected to take on the role of a trusted and accessible mentor within the team, helping supervise more junior team members. Additionally, you will be supported in complementing your core research in ways that interest you and benefit the group, as well as the wider academic community: for example, by collaborating or engaging with policy, charity, or stakeholder organisations; by developing or maintaining open-source and/or community resources and/or by advocating for improved research practices. We welcome applications from those wishing to work part-time.


The post holder should be available to start between October and December 2024 for a duration of 32 months.


Note: We will interview for the role on the 27th of August 2025. We are able to sponsor visas.

Experience:

The ideal candidate will have extensive knowledge of relevant research and methodology, e.g. experience fitting Reinforcement Learning models or applying Agent Based Modelling to human behavioural data. You should have a deep understanding of the strengths and limitations of these approaches, and how to generate robust inferences. We would expect you to be highly skilled at using programming languages such as R or Python.


It is important for you to have a track record of implementing challenging analyses, overcoming statistical problems, producing high-quality visualisations and outputs, and delivering reproducible analysis scripts. You also need a strong track record of delivering high-quality written work at appropriate timescales and managing competing tasks.


For the complete essential and desirable criteria please see the job specification provided as part of the application pack.


We encourage applicants from backgrounds traditionally marginalised and/or under-represented in the field.


If you have any informal enquiries please feel free to contact Dr Amy Orben: amy.orben@mrc-cbu.cam.ac.uk.


Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.


Applicants must have (or be close to obtaining) a PhD.


Appointment at Research Associate level is dependent on having a PhD. Those who have submitted but not yet received their PhD will initially be appointed as a Research Assistant (Grade 5, Point 38 34,132) moving to Research Associate (Grade 7) upon confirmation of your PhD award.


Please ensure that you upload a covering letter and CV in the Upload section of the online application. The covering letter should outline how you match the criteria for the post and why you are applying for this role. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application.


Please include details of your referees, including email address and phone number, one of which must be your most recent line manager.


Please quote reference SU46632 on your application and in any correspondence about this vacancy.


The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.


The University has a responsibility to ensure that all employees are eligible to live and work in the UK.