Fully funded PhD positions

University of St Andrews, University of Bonn; United Kingdom; On-site; GBP 80,000 - 100,000; Full time

Job summary

Two leading academic institutions in the UK are offering fully-funded PhD positions in Psychology and Neuroscience. The projects involve computational modeling and deep learning applications related to behavioral analysis. Ideal candidates will hold a relevant Bachelor's degree and have strong programming skills. Successful applicants will work with experts and develop innovative models and tools, starting in the 2026-2027 academic calendar.

Benefits

Fully funded PhD program

Qualifications

• Experience in computational modeling and statistical analysis.
• Familiarity with deep learning frameworks.
• Strong programming skills in Python or equivalent.

Responsibilities

• Develop multi-scale models to explain brain network adaptations.
• Create deep-learning tools for behavioral analysis.
• Contribute to new collaborations in computational neuroscience.

Skills

Computational modeling

Deep learning

Graph neural networks

Education

Bachelor's degree in Neuroscience, Psychology, Computer Science, or related field

Job description

Employment Start Date: 28 September 2026

Contract Length: 4 years

Country: United Kingdom

Institution: University of St Andrews, University of Bonn

Department: Psychology and Neuroscience

Description:

We investigate how the brain produces behaviour by looking at how movements are generated and adjusted to meet animals’ needs. We currently have two fully-funded PhD projects available, starting at any point during the 2026-2027 academic calendar.

Both have a computational focus and are new collaborations for the lab. The first, in collaboration with Prof Tatjana Tchumatchenko (University of Bonn ), involves building a multi-scale model to explain how cerebelllar networks adapt their according to stimulus novelty and salience.

In the second, in collaboration with Dr David Harris-Birtill (University of St Andrews ), the student will further develop a deep-learning based behavioural analysis tool. We aim to build a multi-modal graph neural network-based approach building on previous work that fuses information from animal pose and clues from audio and video to classify behaviour and relate it to the animal’s environment and other animals present in the recording.

Please send informal enquiries to: mfz [at] st-andrews.ac.uk.

Fully funded PhD positions
14 Westburn Ln, St Andrews KY16 9UU, UK