Research Associate in Machine Learning and Computational Psychiatry for Digital Mental Health Interventions

About the role:

Are you a researcher who wants to do serious machine learning in a domain that matters? We are seeking an exceptional Postdoctoral Research Associate to join MindCraft, an innovative programme at Imperial College London developing AI-guided smartphone-based mental health interventions for adolescents. You will work at the intersection of machine learning, computational psychiatry, digital phenotyping, and real-world intervention research — building mathematically grounded, personalised AI systems that can infer mental state from multimodal behavioural data and learn to deliver the right intervention at the right time.

What you would be doing:

You will play a central role in developing the project’s computational and machine learning core. Your work will include:

• Developing multimodal models of adolescent mental state from longitudinal mobile and self-report data
• Designing latent-state, state-space, probabilistic, or representation-learning approaches for modelling mental health trajectories
• Building personalised digital twin models integrating behavioural, contextual, and questionnaire-derived information
• Developing reinforcement learning, contextual bandit, or sequential decision-making models for adaptive intervention delivery
• Tackling core challenges such as partial observability, uncertainty, missingness, delayed rewards, and non-stationarity
• Contributing to the prospective deployment and evaluation of AI-driven interventions within a real-world school-based study

Depending on your strengths, the role may lean more heavily toward probabilistic and dynamical modelling, reinforcement learning, multimodal representation learning, or computational behavioural modelling.

What we are looking for:

We are especially interested in candidates who combine mathematical maturity, serious implementation ability, and scientific curiosity about mind and behaviour. You should hold, or be close to completing, a PhD in machine learning, computer science, computational neuroscience, computational psychiatry, applied mathematics, statistics, engineering, physics, or a related quantitative discipline.

You should have expertise in one or more of: probabilistic modelling, time-series modelling, latent-variable models, state-space models, reinforcement learning, sequential decision-making, representation learning, Bayesian methods, or computational models of behaviour. Strong Python and deep learning framework skills (PyTorch, JAX, or TensorFlow) are essential. Experience with healthcare, mental health, or mobile sensing data is highly desirable but not required.

What we can offer you:

• The opportunity to work on hard machine learning problems with genuine scientific depth and real-world clinical consequence, not just pipeline engineering.
• Access to rich longitudinal data from an ongoing adolescent mental health study involving 700+ participants, with a rare opportunity to move beyond offline modelling into prospective, real-world adaptive intervention. https://www.imperial.ac.uk/early-career-researcher-institute
• A highly interdisciplinary research environment working closely with clinicians, psychiatrists, and behavioural scientists, with a clear route toward meaningful clinical impact for adolescent mental health.
• Sector-leading salary and remuneration package (including 41 days off a year and generous pension schemes).
• Be part of a diverse, inclusive and collaborative work culture with various staff networks and resources to support your personal and professional wellbeing.

Further Information

*Please note that this is a PhD level role but candidates who have not yet been officially awarded will be appointed as a Research Assistant (£43,863 - £47,223)

MindCraft sits within the Departments of Computing and Bioengineering at Imperial College London, in close collaboration with the Department of Brain Sciences. The project is embedded in an ethically approved trial infrastructure, creating a rare opportunity to develop and evaluate computationally principled adaptive digital mental health systems with a clear route toward meaningful clinical impact.

This is a full-time, fixed-term post 36 months. (35 hours per week).

If you require any further details about the role, please contact: [Professor Aldo Faisal] – [].