AI-informed adaptive mid-field MRI for personalized treatment of depression

AcademicTransfer; Nederland; On-site; EUR 42,000 - 65,000; Full time

Benefits offered by this job

End-of-year bonus (8.3%)

Public transport reimbursement

Bike scheme

BeFrank pension

Job summary

Amsterdam UMC Research BV is seeking a postdoctoral researcher to investigate adaptive, AI-informed mid-field MRI for predicting antidepressant treatment outcomes. You will combine AI, brain imaging and digital mood data to develop biomarkers that enable precision psychiatry and more accessible care.

You will build end-to-end prediction pipelines and translate them into adaptive MRI strategies that run on the scanner, with a pilot study in healthy volunteers and collaboration with academia and

Qualifications

• PhD in a relevant field (AI, CS, biomedical engineering, physics, computational neuroscience or technical medicine).
• Strong programming skills and experience with modern ML workflows.
• Interest in AI, MRI/medical imaging, reinforcement learning and health data science.

Responsibilities

• Adapt predictive models to mid-field perfusion MRI for predicting antidepressant treatment outcomes.
• Develop an AI-based prediction pipeline combining MRI and clinical/digital data.
• Design and test adaptive MRI acquisition strategies, including prototype models on the scanner.
• Conduct a pilot MRI study in healthy volunteers and translate methods into the PRESS platform.

Skills

Python

PyTorch

TensorFlow

Machine learning

MRI/Medical imaging

Reinforcement Learning

Clinical prediction modelling

English proficiency

Education

PhD in AI/CS/ Biomedical Engineering/ Physics/ Computational Neuroscience/ Technical Medicine

Tools

Python libraries

Job description

Organisation/Company Amsterdam UMC Research Field Engineering » Biomedical engineering Engineering » Computer engineering Medical sciences » Medicine Researcher Profile Recognised Researcher (R2) Application Deadline 10 Nov 2026 - 22:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Hours Per Week 36.0 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

Depression affects many people, but antidepressant treatment does not work equally well for everyone. Predicting treatment outcomes early could help clinicians make more informed decisions and tailor treatment to individual patients.

In this postdoc project, you will investigate how adaptive, AI-informed mid-field MRI, guided by questionnaire data, can provide clinically useful biomarkers for predicting antidepressant treatment outcomes. By combining artificial intelligence, brain imaging and digital mood and symptom data, you will work towards a more affordable and widely accessible approach to precision psychiatry.

You will focus on three main areas:

• Exploring how adaptive mid-field MRI can reduce scan time and improve prediction performance compared with fixed scanning protocols, while remaining feasible in outpatient clinics and settings with limited resources.
• Designing an MRI-based prediction pipeline using perfusion measurements from relevant brain regions, acquired with arterial spin labelling (ASL).
• Developing adaptive MRI acquisition methods in which AI models, including reinforcement learning, determine what to scan next based on the information already collected.

You will build on data from a large randomized clinical trial on treatment outcomes in major depressive disorder. Using these data, you will adapt existing prediction models and investigate whether mid-field perfusion MRI can support the early prediction of antidepressant treatment outcomes.

You will develop an end-to-end prediction pipeline and translate your methods into an adaptive MRI strategy that can run directly on the scanner. You will also design and conduct a pilot MRI study in healthy volunteers, testing a prototype model deployed on the scanner.

In addition, you will share your findings with the scientific community and contribute to the further development of the PRESS platform in collaboration with consortium partners from academia and industry. Your responsibilities include:

• Adapting existing predictive models to explore the feasibility of mid-field perfusion MRI for predicting antidepressant treatment outcomes.
• Developing an AI-based prediction pipeline that combines MRI perfusion measurements with relevant clinical and digital data.
• Implementing and testing adaptive mid-field MRI acquisition strategies, including a prototype model deployed on the scanner.
• Designing and conducting a pilot MRI study in healthy volunteers.
• Writing scientific papers, presenting your findings at international conferences and contributing to the integration of your methods into the PRESS platform.

You have a PhD in artificial intelligence, computer science, (biomedical) engineering, physics, computational neuroscience, technical medicine or a closely related field. You enjoy developing new technical approaches and applying them to clinically relevant challenges.

In addition, you bring:

• Strong programming skills, for example in Python, PyTorch or TensorFlow, and experience with modern machine learning workflows.
• An affinity with, and preferably experience in, one or more of the following areas: MRI or other medical imaging, reinforcement learning or sequential decision-making algorithms, and clinical prediction modelling or health data science. Experience with perfusion imaging or ASL is an advantage.
• A clear interest in mental health, neuroimaging and translational research at the intersection of AI and medicine.
• Excellent written and spoken English, good communication skills and the ability to work independently and proactively in a multidisciplinary research environment.

Additional Information

• You will be employed by Amsterdam UMC Research BV.
• A contract for 12 months.
• Classification in salary scale 10: € 3.724 to € 5.867 gross for full-time employment (depending on experience). In addition to a good basic salary, we offer 8.3% end-of-year bonus. Calculate your net salary here .
• Holiday hours: 194.4 per year for full time and a possibility to save additional hours.
• 100% reimbursement for public transport travel costs. If you travel by foot, bicycle, or car, a mileage allowance of €0.21 per km applies (up to a maximum of 40 km one way by car).
• Do you prefer walking or cycling? Take advantage of our good bike scheme.
• Pension accrual with BeFrank, a modern, comprehensible and fairly priced pension.

Watch this video with more information about joining Amsterdam UMC Research BV.

Additional comments

The first round of interviews is expected to take place during the first two weeks of December. Please keep this in mind when planning your availability. The second round will follow shortly after the first.

During the publication period, applications will be handled continuously. If the vacancy is filled, it will be closed prematurely.

Do you have any questions? For further information about this position, please contact Prof. Liesbeth Reneman, at [e-mail] or Matthan Caan, PhD, at [e-mail].

A reference check, screening and hiring assessment may be part of the procedure. If you join us, we ask you for a VOG (Certificate of Good Conduct).

Internal candidates will be given priority over external candidates in case of equal suitability.