PhD position Data Science

University of Groningen; Netherlands; On-site; EUR 36,000 - 48,000; Full time

Benefits offered by this job

Vacation hours

End-of-year bonus

Professional development

Job summary

The University of Groningen invites applications for a PhD position in an international, interdisciplinary project focused on digital proxies of Reward, Motivation and Impulsivity (RM&I). You will develop data-driven measures and connect them with neurobiological markers to advance precision medicine.

As a PhD candidate, you will conduct systematic reviews, build and apply digital proxies, and test hypotheses across disorders such as MDD, AD and obesity, collaborating with longitudinal cohorts

Qualifications

• Completed Master's degree in a relevant field (data science, neuroscience, psychology, biomedical sciences, etc.)
• Strong interest in applying quantitative and computational approaches to biomedical or clinical research.
• Experience with statistical analysis and/or data science.
• Programming experience in R and/or Python.
• Interest in digital phenotyping, digital biomarkers, behavioural data or other digital measures.

Responsibilities

• Systematic review of digital proxies related to RM&I across conditions.
• Development and application of data-driven digital proxies in longitudinal datasets.
• Investigation of relationships between digital proxies and neurobiological markers.
• Coordinate interdisciplinary analyses and communicate findings clearly.

Skills

R programming

Python programming

Data science

English proficiency

Analytical skills

Scientific writing

Education

Master's degree

Tools

R

Python

Job description

Psychological sciences » Behavioural sciences

Psychological sciences » Cognitive science

Computer science » Programming

Organisation/Company University of Groningen Research Field Neurosciences » Neurobiology Neurosciences » Neuropsychology Psychological sciences » Behavioural sciences Psychological sciences » Cognitive science Computer science » Programming Researcher Profile First Stage Researcher (R1) Application Deadline 29 Oct 2026 - 23:00 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Hours Per Week 38.0 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

Are you interested in using data science to understand how digital measures can capture clinically meaningful aspects of reward, motivation and impulsivity? Do you want to develop and apply innovative digital proxies and combine them with neurobiological markers to advance precision medicine across mental and metabolic health conditions? Then this PhD position in an international pioneering project may be an excellent opportunity for you.

You will work in an interdisciplinary, international research project aiming to advance a transdiagnostic precision-medicine framework centred on Reward, Motivation and Impulsivity. The project brings together expertise in longitudinal research, biomarker discovery, clinical validation, data science, evidence synthesis and stakeholder engagement.

A central ambition is to move beyond disease-specific approaches by identifying biological, behavioural and digital markers that can help characterise clinically meaningful processes across different health conditions.

As a PhD candidate, you will contribute to this ambition by helping establish the evidence base for digital proxies, developing and applying data-driven measures, and investigating their relationships with neurobiological markers.

What are you going to do?

We are looking for an ambitious and analytically minded PhD candidate to investigate digital proxies of Reward, Motivation and Impulsivity (RM&I) and their relationship with neurobiological markers and clinically relevant outcomes.

Your work will be connecting systematic evidence synthesis, data science, longitudinal research and clinical validation. Your research will contribute to understanding whether and how digital measures can provide scalable and meaningful proxies for RM&I-related processes across major depressive disorder (MDD), Alzheimer’s disease (AD), and obesity (OB).

Your PhD research will have three closely connected components:

• Systematic review of digital proxies: You will systematically synthesise existing evidence on digital proxies relevant to RM&I, identifying the types of digital measures that have been investigated, their relationship with behavioural and clinical constructs, and their potential relevance for transdiagnostic research.
• Development and application of digital proxies: You will use data-science approaches to develop, characterise and/or evaluate RM&I-related digital proxies. You will subsequently apply these digital proxies to analyses conducted within the project's longitudinal and clinical datasets, contributing to the identification of meaningful patterns across individuals and disease trajectories.
• Hypothesis testing with neurobiological markers: You will investigate relationships between digital proxies and neurobiological markers, testing hypotheses about the biological mechanisms underlying RM&I-related processes. Depending on the available data and the development of the research, this may involve integrating digital, behavioural, clinical and neurobiological measures.

An important aspect of your work will be to examine the clinical and transdiagnostic relevance of digital proxies. You will contribute to determining whether digital measures can complement existing biomarkers and endpoints and help identify measurable features of RM&I that are relevant across different conditions.

You will work closely with researchers involved in longitudinal cohort analyses, clinical studies, biomarker research and evidence synthesis. Your work will therefore sit at the intersection of data science, digital phenotyping, clinical research and neurobiology.

We are looking for a motivated researcher with a strong interest in data science, digital proxies, biomarkers and clinical research.

You have:

• A completed Master's degree in a relevant field such as data science, artificial intelligence, computer science, neuroscience, psychology, biomedical sciences, medicine, epidemiology, health sciences or a related discipline.
• A strong interest in applying quantitative and computational approaches to biomedical or clinical research.
• Experience with statistical analysis and/or data science.
• Programming experience, preferably in R and/or Python.
• An interest in digital phenotyping, digital biomarkers, behavioural data or other digital measures.
• The ability to critically assess and synthesise scientific literature.
• Strong analytical and problem-solving skills.
• Good scientific writing and communication skills.
• The ability to work independently while contributing effectively to an interdisciplinary team; and
• Excellent written and spoken English.

Experience with one or more of the following would be an advantage:

• Systematic reviews or evidence synthesis.
• Longitudinal or cohort data analysis.
• Multimodal or multi-omics data.
• Machine learning or other data-science methods.
• Digital phenotyping or development of digital biomarkers/proxies.
• Neuroimaging, electrophysiology or other neurobiological measures.
• Behavioural or cognitive measures.
• Reproducible research and open-science practices; and
• Research involving MDD, AD, obesity, RM&I or related transdiagnostic constructs.

We particularly value candidates who are curious about how digital measures can be linked to underlying neurobiological processes and translated into meaningful research outcomes.

Additional Information

What can you expect from us?

• 232 vacation hours per year, based on a 38-hour workweek (1.0 FTE). You can also work more or fewer hours in exchange for more or fewer free hours. For example, with a 40-hour workweek, you save 96 extra free hours, and with a 36-hour workweek, you lose 96 hours.
• End-of-year bonus of 8.3% and 8% holiday allowance.
• Extensive opportunities for personal and professional development.

Selection process

Interested?

Information about applying

When scheduling meetings, we will take your schedule into account as much as possible. The University of Groningen considers social safety important. We strive to be a university where staff and students feel respected and at home, regardless of differences in background, experiences, perspectives, and identity. For more information, see also our page about our diversity policy.

Our selection procedure follows the guidelines of the NVP application code

Additional comments

Do you have any questions or need more information?

Questions about the content of the job?
Martien Kas (Full Professor): [e-mail]

Questions about your application process?
Martien Kas (Full Professor): [e-mail]