PHD Position

This PhD position investigates EEG and neurobiological markers related to reward, motivation, and impulsivity across major depressive disorder, Alzheimer's disease, and obesity. The research combines three connected components: a systematic review of EEG measures, empirical EEG analyses of cohort and clinical data, and hypothesis-driven research linking EEG to other neurobiological markers. The project connects evidence synthesis with empirical work to contribute to a transdiagnostic precision medicine framework and to develop expertise in EEG methodology and quantitative analysis.

• Master's degree in neuroscience, biomedical sciences, psychology, cognitive science, medicine, biology, behavioural science, or a related discipline.
• Strong interest in human neurobiology and EEG research.
• Experience with quantitative research, statistical analysis, and scientific literature review.
• Practical experience with EEG data collection, preprocessing, analysis, or interpretation, and familiarity with EEG-derived measures.
• Experience with EEG analysis software or programming environments such as MATLAB, Python, or R.
• Experience with statistical modelling and other quantitative analytical approaches.
• Experience working with clinical, cohort, or population-based datasets, and with multimodal or longitudinal data where applicable.
• Experience conducting systematic or scoping reviews and familiarity with systematic-review methodology, literature searching, screening, and data extraction.
• Experience with biological or neurobiological markers and knowledge of reward, motivation, or impulsivity processes.
• Experience with open and reproducible research practices.
• Excellent written and spoken English; strong analytical and problem-solving skills.
• Ability to work systematically and accurately with complex datasets, to work independently, and to collaborate within a multidisciplinary research team.
• Strong motivation to develop as an independent researcher and complete a PhD within four years. Experience in all listed areas is not required; scientific curiosity and willingness to learn new methods are valued.

• Develop and conduct a systematic review of EEG measures relevant to reward, motivation, and impulsivity, including search strategies, eligibility criteria, data extraction, and evidence synthesis.
• Extract, organise, and map information on EEG measures, study characteristics, populations, outcomes, and relevant neurobiological markers.
• Identify promising EEG measures and gaps in the existing evidence; contribute to publications from the evidence synthesis.
• Prepare, preprocess, and perform quality control on EEG datasets; develop reproducible and well-documented analytical workflows.
• Investigate EEG measures (e.g., event-related potentials, spectral and time-frequency measures) relevant to reward, motivation, and impulsivity.
• Examine associations between EEG measures and behavioural, clinical, biological, and phenotypic variables across different populations and research settings.
• Formulate and test hypotheses concerning relationships between EEG and other neurobiological markers, applying appropriate statistical methods.
• Investigate whether combinations of neurobiological measures provide complementary information and whether markers relate to transdiagnostic dimensions or clinical outcomes.
• Interpret findings in the context of existing evidence and the precision medicine framework; communicate results through scientific publications, presentations, and meetings.
• Progressively develop methodological independence and contribute to analytical and interpretative decisions under supervisory guidance.

• End-of-year bonus of 8.3% and 8% holiday allowance.
• Extensive opportunities for personal and professional development.
• Temporary appointment for 1.0 FTE for four years.
• This position is conditional upon the grant agreement being signed and associated funding becoming available.

You will be based at the University of Groningen, within the GELIFES institute Neurobiology expertise group and the Faculty of Science and Engineering. The faculty performs interdisciplinary research across disciplines such as physics, biology, artificial intelligence, mechanical engineering, and pharmacy, and collaborates with industry, healthcare, government, and societal partners.

The research environment brings together expertise in neuroscience, evidence synthesis, data analysis, and precision medicine, and involves collaboration with academic and clinical researchers in an international research consortium. The research programme aims to develop a transdiagnostic precision medicine framework for reward, motivation, and impulsivity across major depressive disorder, Alzheimer's disease, and obesity.