PhD in Statistical Bioinformatics

As one of the largest and most dynamic academic communities in the Netherlands, the department Mathematics and Computer Science (M&CS) brings together more than 140 scientific staff, over 250 PhD and EngD candidates, and nearly 3000 students. We collaborate closely with leading industrial partners in the Brainport Eindhoven region and with universities across the globe—creating a uniquely fertile environment for both fundamental breakthroughs and applied innovation. Introduction Are you our next PhD candidate in statistical data integration? Are you passionate about statistical methodology and motivated by biomedical applications? Join our team on development of latent variable models for multi‑omics and longitudinal data and help advance data‑driven insights. Job Description Statistical modelling of multiple omics datasets is a lively and rapidly developing research area. Ongoing technological advances make it possible to measure multiple biological data types that reflect related biological mechanisms, such as proteomics, metabolomics, and transcriptomics. Latent variable models are widely used for identifying the underlying structure in such high-dimensional data and for dimension reduction. Recent methodological developments have extended probabilistic principal component models to settings involving multiple datasets, for datasets spanning biobanks, and for longitudinal designs. Some of these latent models capture also dataset‑specific components, account for heterogeneity of the joint components across datasets, or incorporate covariates. However, comparable flexible models for longitudinal data are still lacking. Moreover, it remains unclear how to assess whether simpler latent variable models adequately fit these complex datasets. During this PhD project, you will develop methods to assess goodness-of-fit for latent variable models for multiple omics datasets and develop flexible models for longitudinal designs. You will apply your approaches to several available omics datasets, both open-source and provided by collaborators, and you will develop R packages to implement the methods. By improving model assessment and interpretability, your work will contribute to deeper insights into biological pathways and disease mechanisms, ultimately supporting advances in diagnosis, treatment selection, and monitoring in healthcare. You will present your work to the statistical community and to collaborators from applied domains. You will join the Statistics group within the cluster Statistics, Probability, and Operations Research (SPOR). The group focuses on developing sound statistical models and methodology for the data-driven analysis of complex and dynamic systems, with the goal of enabling predictive, prescriptive, and pre‑emptive analytics. We work closely with external partners who drive innovation and growth, and our research is strongly embedded in applications such as anomaly detection, process monitoring and improvement, weather and climate forecasting, and statistical bioinformatics. As an ideal candidate, you have a strong affinity for mathematics, combined with an interest in applications in the biomedical domain and an openness toward interdisciplinary collaboration. Job Requirements

• A motivated, enthusiastic, curiosity-driven researcher.
• A master’s degree (or an equivalent university degree) in Mathematics, Statistics, or a closely related field.
• Experience in analysis of biological datasets is of benefit.
• Interest to work in an interdisciplinary project.
• Motivated to develop your teaching skills and coach students.
• Excellent communication skills.
• Fluent in spoken and written English (at least C1 level).

Conditions of Employment A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:

• Full-time employment for four years, with an intermediate assessment after nine months. You will spend a minimum of 10% of your four-year employment on teaching tasks, with a maximum of 15% per year of your employment.
• Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. € 3,059 - max. € 3,881).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
• An excellent technical infrastructure, on-campus children's day care and sports facilities.
• Unlimited access to the modern on‑campus TU/e Student Sports Center at an exceptionally affordable rate.
• An allowance for commuting, working from home and internet costs.
• A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.

On our website you can discover even more information about our conditions of employment. Build on your career at TU/e! About us We are a leading international university where scientific curiosity meets a hands-on mindset. We work in an open and collaborative way with high-tech industries to tackle complex societal challenges. Our responsible and respectful approach ensures impact — today and in the future. TU/e is home to over 13,000 students and more than 7,000 staff, forming a diverse and vibrant academic community. Our university is located in Brainport Eindhoven — a world‑leading tech region with more than 7,000 high‑tech companies and strong R&D activity. Known for breakthroughs in AI, photonics, semiconductors and advanced manufacturing, Brainport is a place where technology serves people and society. Learn more about the Brainport region here. As one of the largest and most dynamic academic communities in the Netherlands, the department Mathematics and Computer Science (M&CS) brings together more than 140 scientific staff, over 250 PhD and EngD candidates, and nearly 3000 students. We collaborate closely with leading industrial partners in the Brainport Eindhoven region and with universities across the globe—creating a uniquely fertile environment for both fundamental breakthroughs and applied innovation. Information Do you recognize yourself in this profile and would you like to know more? Please contact the hiring manager Prof.dr. Jeanine Duistermaat, j.j.duistermaat@tue.nl. Visit our website for more information about the application process. You can also contact HR services M&CS, hrservices.mcs@tue.nl. Curious to hear more about what it’s like as a PhD candidate at TU/e? Please view the video. Are you inspired and would like to know more about working at TU/e? Please visit our career page. Application We invite you to submit a complete application by using the apply button. The application should include a:

• Cover letter in which you describe your motivation and qualifications for the position.
• Curriculum vitae, including a list of your publications and the contact information of three references. Kindly note that we may reach out to references at any stage of the recruitment process. We recommend notifying your references upon submitting your application.

Ensure that you submit all the requested application documents. We give priority to complete applications.

We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled. Please note

• You can apply online. We will not process applications sent by email and/or post.
• A pre-employment screening (e.g. knowledge security check) can be part of the selection procedure. For more information on the knowledge security check, please consult the National Knowledge Security Guidelines.
• Please do not contact us for unsolicited services.

Type of employment: temporary position | Contract type: full time | Number of positions: 1 | Full-time equivalent: 1.0 FTE | City: Eindhoven | County: Noord-Brabant | Country: Netherlands | Reference number: 2026/253 | Published: 2026-04-17 | Last application date: 2026-05-17