PhD position EEG and Neurobiological Markers

We are looking for an enthusiastic PhD candidate to join an international, multidisciplinary research programme investigating reward, motivation, and impulsivity across major depressive disorder, Alzheimer's disease, and obesity.

Your PhD research will combine three closely connected components: a systematic review of EEG measures, empirical EEG analyses, and hypothesis-driven research investigating relationships between EEG and other neurobiological markers.

The position provides an opportunity to develop expertise in EEG methodology and quantitative analysis while contributing to a broader precision medicine approach that integrates evidence across different populations, research settings, and types of biological and clinical data.

What are you going to do?

Your PhD research will connect systematic evidence synthesis with empirical EEG research and hypothesis-driven investigation of neurobiological markers.

Systematic review of EEG measures

A first component of your research will be a systematic review of EEG measures relevant to reward, motivation, and impulsivity.

You will:

• Develop and conduct a systematic review of EEG measures relevant to reward, motivation, and impulsivity.
• Define and document search strategies and eligibility criteria.
• Screen and select relevant scientific literature.
• Extract and organise information on EEG measures, study characteristics, populations, outcomes, and relevant neurobiological markers.
• Synthesise and map the available evidence in a transparent and reproducible manner.
• Investigate the consistency and potential relevance of different EEG measures across populations and research settings.
• Identify promising EEG measures as well as important gaps in the existing evidence.
• Contribute to scientific publications and other outputs arising from the evidence synthesis.

This work will provide an evidence-based foundation for the interpretation and selection of EEG measures used in the empirical research.

EEG analyses

A substantial part of your PhD will involve analysing EEG data generated through cohort and clinical research.

Depending on the available datasets and specific research questions, you will:

• Contribute to the preparation, preprocessing, and quality control of EEG data.
• Develop and apply appropriate EEG analysis pipelines.
• Investigate EEG measures relevant to reward, motivation, and impulsivity.
• Examine associations between EEG measures and behavioural, clinical, and other relevant variables.
• Analyse data collected across different populations and research settings.
• Contribute to the development of reproducible and well-documented analytical workflows.
• Interpret EEG findings in the context of the broader scientific framework.
• Communicate findings through scientific publications, presentations, and research meetings.

You will progressively develop methodological independence and contribute to decisions concerning the analysis and interpretation of EEG data under the guidance of the supervisory team.

Hypothesis testing with neurobiological markers

A further aim of the PhD is to investigate hypothesis-driven relationships between EEG measures and other neurobiological markers.

You will:

• Formulate and test hypotheses concerning relationships between neurobiological markers relevant to reward, motivation, and impulsivity.
• Investigate associations between EEG measures and other available biological, clinical, behavioural, or phenotypic measures.
• Examine whether neurobiological markers are associated with transdiagnostic dimensions of reward, motivation, and impulsivity or with relevant clinical outcomes.
• Apply appropriate statistical methods to test predefined hypotheses.
• Investigate whether combinations of neurobiological measures provide complementary information.
• Interpret findings in relation to existing evidence and the broader precision medicine framework.
• Contribute to understanding the potential of neurobiological markers for characterising clinically relevant profiles across different conditions.

The precise analytical approaches will be developed in collaboration with the supervisory team and will depend on the available datasets and scientific questions.

Integration of evidence and empirical research

An important feature of the PhD is the connection between what is known from the literature and what can be learned from new data.

You will therefore have the opportunity to:

• Use findings from the systematic review to inform empirical EEG analyses.
• Compare findings across different populations and research settings.
• Integrate EEG findings with other neurobiological, behavioural, and clinical measures.
• Critically evaluate the strengths and limitations of candidate biomarkers.
• Contribute to the identification of neurobiological measures that may have relevance across diagnostic categories.

This integrated approach will allow you to develop a broad understanding of how EEG and other neurobiological measures can contribute to transdiagnostic and precision medicine research.

Requirements

We are looking for a highly motivated candidate with a strong interest in neuroscience, EEG, and quantitative research.

You have:

• A Master's degree in neuroscience, biomedical sciences, psychology, cognitive science, medicine, biology, behavioural science, or a related discipline.
• A strong interest in human neurobiology and EEG research.
• Experience with quantitative research and statistical analysis.
• Experience with scientific literature and academic research.
• Strong analytical and problem-solving skills.
• The ability to work systematically and accurately with scientific literature and complex datasets.
• Excellent written and spoken English.
• The ability to work independently while collaborating effectively within a multidisciplinary research team.
• A strong motivation to develop as an independent researcher and complete a PhD within four years.

You do not need to be an expert in all EEG methodologies. We are particularly interested in candidates who have a strong scientific and quantitative foundation, some relevant experience with EEG or neurophysiological research, and the motivation to develop further methodological expertise during the PhD.

It is an advantage if you have

• Practical experience with EEG data collection, preprocessing, analysis, or interpretation.
• Familiarity with EEG-derived measures, such as event-related potentials, spectral measures, or time-frequency measures.
• Experience with EEG analysis software or programming environments such as MATLAB, Python, or R.
• Experience with statistical modelling or other quantitative analytical approaches.
• Experience working with clinical, cohort, or population-based datasets.
• Experience with multimodal or longitudinal data.
• Experience conducting systematic or scoping reviews.
• Familiarity with systematic-review methodology, literature searching, screening, and data extraction.
• Experience with biological or neurobiological markers.
• Knowledge of reward, motivation, impulsivity, or related cognitive and affective processes.
• Experience with open and reproducible research practices.

Experience in all of these areas is not required. We value scientific curiosity, methodological foundations, analytical thinking, and the ability and motivation to learn new methods.

Conditions of employment

Fixed-term contract: Temporary appointment for 1.0 FTE for 4 years.

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

University of Groningen

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.

Department

Faculty of Science and Engineering

The Faculty of Science and Engineering (FSE) provides teaching and research across a wide range of disciplines, from physics and biology to artificial intelligence, mechanical engineering, and pharmacy. In close collaboration with partners from industry, healthcare, and society, we contribute to the urgent challenges of our time, such as energy, sustainability, digitization, and medical technology. Our community is open and informal, with more than 7,000 students, 1,000 PhD students, and 1,400 staff members from all over the world. If you would like to learn more about the Faculty of Science and Engineering, visit rug.nl/fse.

You will be based at the University of Groningen and become part of the GELIFES institute Neurobiology expertise group. You will work within an interdisciplinary research environment bringing together expertise in neuroscience, evidence synthesis, data analysis, and precision medicine.

The research involves collaboration with academic and clinical researchers and other partners in an international research consortium.

About the research programme

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. The programme combines cohort research, clinical studies, biomarker research, systematic evidence synthesis, and stakeholder engagement. It seeks to identify and evaluate measures that can improve the understanding and characterisation of reward, motivation, and impulsivity across different conditions. Your PhD will contribute specifically to the investigation of EEG and other neurobiological markers. By combining systematic evidence synthesis with empirical EEG analyses and hypothesis-driven research, you will contribute to understanding the potential value of neurobiological measures within a transdiagnostic precision medicine framework.

This position is conditional upon the grant agreement being signed and the associated funding becoming available.

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

Working at University of Groningen

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