Project Description
Would you like to develop AI-based methods to understand and predict recovery after traumatic brain injury? We welcome applications for a researcher position at Uppsala University.
The Department of Medical Sciences is a large clinical institution with more than 250 employees and over 900 additional coworkers connected via the Uppsala University Hospital. The Department of Medical Sciences has a broad research profile with strong research groups in a number of different areas. The research carried out at the department is performed in close connection with the clinical activities at the Uppsala University Hospital, which includes both basic studies on the causes of a variety of illnesses and the development and evaluation of improved diagnostics and new treatment methods. More information about the Department of Medical Sciences can be found at Medical sciences.
The neurotrauma research group at Uppsala University and Uppsala University Hospital conducts clinical and translational research focusing on individual differences in recovery following traumatic brain injury. Our research combines clinical patient data, continuous physiological monitoring from neurocritical care, neuroimaging and advanced data analytics. This project aims to develop and validate AI-based models for dynamic outcome prediction and improved understanding of secondary brain injury, with the long-term goal of supporting personalised care.
Duties
The position involves developing, implementing and evaluating machine learning and artificial intelligence methods for research data from patients with traumatic brain injury (TBI). Main duties include:
- Processing and integrating longitudinal clinical data, physiological time series (e.g. ICP, CPP and blood pressure), laboratory data and imaging-derived variables.
- Developing and externally validating predictive models of clinical outcomes and physiological changes during intensive care.
- Developing reproducible analytical pipelines, quality assurance, documentation and secure data workflows.
- Conducting scientific analyses, preparing manuscripts and presenting findings in interdisciplinary collaboration with clinicians and researchers.
Requirements
PhD in computer science, artificial intelligence, machine learning, bioinformatics or another field relevant to the position.
- Documented experience developing and evaluating machine learning or deep learning models.
- Strong Python programming skills and experience with relevant machine learning frameworks, such as PyTorch.
- Experience in quantitative data analysis and scientific research, including the ability to document and communicate results.
- Ability to work independently and in interdisciplinary teams, and excellent English communication skills.
Additional qualifications
- Experience in generative artificial intelligence, including diffusion models, synthetic data generation and data augmentation techniques.
- Experience in high-performance computing (HPC), GPU acceleration, and the development and optimization of scalable machine learning and deep learning workflows.
- Experience in computer vision, medical or scientific image analysis, and multimodal machine learning involving heterogeneous data sources.
About the employment
The employment is 12 months. Scope: full-time. Starting date: as agreed. Placement: Uppsala.
For further information about the position, please contact:Elham Rostami, elham.rostami@uu.se.
In this recruitment we have replaced the cover letter with questions that you are asked to answer when making your application. The answers will be used as a part of the selection process.
Please submit your application by November 9, 2026, UFV-PA 2026/3235.
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Uppsala University
Uppsala, Sweden