PhD position Data Science

Job 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.

Requirements

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.

Conditions of employment

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.

Employer

At the University of Groningen (UG), researchers from all fields of academia and technology are working on academic challenges and societal questions. Lecturers prepare their students for meaningful careers within or outside the academic world. Interdisciplinary research and teaching, sharing of knowledge, collaboration with businesses, government institutions, and societal organizations are aspects that are of the utmost importance to this European top university. The UG aims to be an open academic community with an inclusive and safe working climate that invites you to add your value.

Additional information

Do you have any questions or need more information?

Questions about the content of the job?
Martien Kas (Full Professor): M.J.H.Kas@rug.nl

Questions about your application process?
Martien Kas (Full Professor): M.J.H.Kas@rug.nl