Research Fellow

The Opportunity:

The Centre for Medical Informatics at the Usher Institute within The University of Edinburgh is looking for a non-clinical Post-doctoral Research Fellow to conduct original research, focusing on the development and application of data analytics methods to process multimodal data to provide clinically useful insights into bipolar disorders. This is part of the £3m 5-year Wellcome Trust Programme Grant, “Ambient and passive collection of sleep and circadian rhythm data in bipolar disorder to understand symptom trajectories and clinical outcomes (AMBIENT-BD)”.

The post holder will be a key member of the Data Analytics Research and Technology Research group (DARTH) led by Prof. Athanasios Tsanas, and the AMBIENT-BD project team.

They will:

1. Focus on the development and application of signal processing and statistical machine learning techniques to mine self-reports and sensor data to gain new insights towards assessment and longitudinal monitoring of bipolar disorder; 
2. Work on sleep datasets exploring the relationship of sleep and mental health; and
3. Engage with clinical collaborators to facilitate translation of findings into clinical practice. 

We will also consider requests for hybrid working (on a non-contractual basis) that combines a mix of remote and regular (weekly) on-campus working.  The Usher Institute expects a minimum of 40% on campus working.

Informal enquiries may be directed to Prof. Thanasis Tsanas, Professor of Digital Health and Data Science (atsanas@ed.ac.uk) 

Your skills and attributes for success:

• PhD or MSc with related work experience in a relevant discipline e.g. Medical Informatics, Engineering, Mathematics, Statistics, Physics, or Computer Science.
• Experience in the application and development of data analytics methods (e.g. time-series analysis, signal processing, statistical machine learning), preferably including some experience on physiological signals, clinical reports/self-reported outcome measures and sensor data.
• Experience working in multi-disciplinary teams, preferably with clinical colleagues.
• Excellent programming skills (MATLAB or Python preferred).
• Proven track record of publishing research outputs.

Apply Before: 01/05/2026, 23:59

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