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Postdoctoral Research Associate in Transdiagnostic Artificial Intelligence

KINGS COLLEGE LONDON

United Kingdom

On-site

GBP 45,000 - 53,000

Full time

8 days ago

Job summary

A leading UK university is seeking a postdoctoral researcher to develop and validate predictive models in mental health using AI. This full-time position offers opportunities to work with multimodal data and collaborate with clinical teams. Ideal candidates have a PhD in a related field and expertise in machine learning. The salary range is £45,031 - £52,514 per annum, with applications closing on 16-Nov-2025.

Qualifications

  • PhD or nearing completion in relevant field.
  • Proven experience with machine learning models.
  • Strong statistical and coding skills.

Responsibilities

  • Develop and validate predictive models using multimodal data.
  • Collaborate across clinical and research teams.
  • Publish findings and engage in research grant activities.

Skills

Machine learning expertise
Statistical analysis
Interdisciplinary interest
Excellent communication skills

Education

PhD in neuroscience, psychology, psychiatry, or biomedical engineering

Tools

MATLAB
Python
R
GitHub
AWS
Azure
Job description
Overview

KING’S COLLEGE LONDON is a world-renowned university delivering education and research across biological and psychological sciences. The IoPPN is a leading centre for mental health and neuroscience research in Europe and the largest in the UK. The Department of Psychosis Studies is a global centre for research into psychotic disorders within the School of Academic Psychiatry. This role sits within the Artificial Intelligence in Mental Health Lab and involves collaboration across AI, neuroscience, and mental health to predict and understand psychosis and affective disorders.

About the role

This is a highly motivated postdoctoral researcher position in the Department of Psychosis Studies at IoPPN, King’s College London. The role involves developing and validating predictive models using multimodal data, including neuroimaging, omics, and digital phenotyping, and building a predictive modelling platform for transdiagnostic comparisons, external validation, and integration into future trials. The postholder will also contribute to opportunities at the intersection of AI and mental health and will work on real-world clinical challenges.

We welcome applicants with a background in psychology, psychiatry, biomedical engineering, or related disciplines who are passionate about applying machine learning to real-world clinical challenges. This is a full-time role (35 hours per week) with a fixed-term contract until 30/06/2028.

Responsibilities
  • Lead the development and validation of predictive models using multimodal data (neuroimaging, omics, and digital phenotyping).
  • Contribute to building and maintaining a predictive modelling platform for testing, hosting, and deploying machine learning models for transdiagnostic comparisons and external validation.
  • Collaborate with clinical and research teams across distributed networks and contribute to interdisciplinary research projects.
  • Prepare and publish research findings in scientific journals and participate in grants, fellowships, and related activities.
Qualifications
  • PhD in neuroscience, psychology, psychiatry, biomedical engineering, or related discipline.
  • Documented expertise and a track record in machine learning across mental and/or neurological disorders data domains.
  • Experience analyzing high-dimensional data (neuroimaging, omics, or temporal data from smartphones/wearables).
  • Strong statistical and coding skills with experience in MATLAB, Python, and/or R.
  • Interdisciplinary interest in mental health and a track record of publishing and project/grant participation.
  • Excellent interpersonal and communication skills for working in distributed networks.
  • Proven experience developing and implementing ML models/algorithms, ideally in healthcare or mental health.
  • Record of grant applications or attempts to obtain funding; experience with ML-based software and deep learning models (CNNs, autoencoders, transformers).
  • Experience with coding/data management tools such as GitHub, DataLad, AWS, or Azure.
  • Demonstrated ability to co-supervise and mentor PhD and MSc students.

Please note that this is a PhD-level role, but candidates who have submitted their thesis and are awaiting the award of their PhDs will be considered. In such circumstances the appointment will be at Grade 5, spine point 30 with the title Research Assistant, and the salary will increase to Grade 6 upon confirmation of the award.

Additional information

Further information includes the option to download the Job Description document from the bottom of the page for full criteria assessment details. Interviews are due to be held on 10/12/2025. The salary range is £45,031 - £52,514 per annum, including London Weighting. Close Date: 16-Nov-2025. Contact Person: Dr Paris Alexandros Lalousis. Contact Details: paris.lalousis@kcl.ac.uk.

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