PhD Optimal Design and Principled Statistical Analysis of SEM- fMRI Connectivity

Welcome to Maastricht University!

Are you interested in statistics and sample size calculations for fMRI research? Join us to develop simulation tools and power analysis methods for fMRI connectivity studies using Structural Equation Modeling!

PhD candidate Optimal Design and Principled Statistical Analysis of SEM-Based fMRI Connectivity – Through Realistic Simulation

• Our goal: this project develops statistical methods to evaluate connectivity models and optimize study design. You will extend a R program to simulate realistic fMRI datasets and build tools for power and sample size analysis. The goal is to enable more reliable, efficient, and scientifically rigorous fMRI research.
• Your colleagues: you will work in the FHML division of the interfaculty Department of Methodology and Statistics (M&S) at FHML and the Faculty of Psychology and Neuroscience. With around 20 staff members, M&S provides statistics education across multiple Bachelor, Master, and PhD programmes and offers statistical support for researchers from both faculties.

In this project you will develop statistical methods and software tools to support the design, planning, and analysis of fMRI studies, including connectivity analysis and activation modelling. Specifically, you will extend the R package neu Rosim to simulate realistic fMRI data with accurate spatial and temporal noise structures, evaluate and compare connectivity models, and develop power analysis and sample size calculation methods for fMRI study designs.

• Conduct a systematic review of fMRI simulation tools, connectivity modelling approaches, and current practices in power analysis and sample size determination.
• Extend the R package neu Rosim with more realistic spatial and temporal noise structures, validated against empirical fMRI data.
• Evaluate and compare SEM-based and network-based connectivity models under realistic simulation conditions, incorporating Bayesian statistical techniques.
• Develop power analysis and sample size calculation methods for fMRI study designs.
• Integrate simulation and optimal design principles into a user‑friendly R‑based software package.
• Present research at conferences and publish results in international methodological journals.
• Do some teaching (maximum 0.1 FTE).

We’re not looking for check boxes; we’re interested in who you are and what you bring. Do you recognise yourself in this?

You take initiative, are creative, possess strong analytical skills, work in an organised and focussed manner, and can work independently while collaborating effectively within a research team.

• Master’s degree in Statistics, Mathematics, Physics, Econometrics, Biostatistics, Psychometrics, or a related quantitative field.
• Excellent statistical programming skills in R, including experience with simulation, as demonstrated by your master’s thesis or other scientific work.
• Solid background in statistical modelling, including structural equation modelling or related multivariate methods.
• Understanding of basic characteristics of fMRI methodology or motivation to learn them quickly; prior experience is an asset.
• Experience with Bayesian statistics and Bayesian computational tools is a plus.
• Experience with evaluating statistical power, sample size, or design efficiency in complex models is a plus.
• Excellent English communication skills (both verbal and written).

• A 12‑month contract (1.0 FTE) with the prospect of a 3‑year extension.
• A gross monthly salary between €3,059 and €3,881 (based on full‑time employment of 38 hours per week). 8 % holiday allowance and an 8.3 % year‑end bonus.
• 29 vacation days (based on full‑time), four additional days off (Carnival Monday and Tuesday, Good Friday, and Liberation Day), and possibility to accrue up to 12 extra days through compensation hours.
• Flexible working hours, a home‑office allowance, and the option to work from home.
• Freedom and space to shape your work independently and develop your ideas.
• A close‑knit community of colleagues to collaborate and grow with.
• A solid pension plan via ABP, company fitness schemes, and access to various university sports facilities.
• An inspiring work environment in the heart of Europe.

The vacancy is open for internal and external candidates. In case of equal qualifications, internal candidates will be prioritised.

Maastricht University is committed to promoting and nurturing a diverse and inclusive community. We believe that diversity in our staff and student population contributes to the quality of research and education, and we strive to enable this through inclusive policies and innovative projects led by teams of staff and students.