Eindhoven University of Technology
Just Landed
New Today
PhD in Statistics: Functional Data Analysis, Time-Varying Networks, and Structural Change Eindhoven University of Technology in Netherlands
Degree Level
PhD
Field of study
Computer Science
Funding
Full-time PhD employment for five years with an intermediate assessment after nine months. Salary is on scale P, approximately €3,204 to €4,051 gross per month for full-time work, plus an 8% holiday allowance and an 8.3% year-end bonus. Benefits include pension contributions, leave, training, commuting/work-from-home/internet allowances, and support for international candidates.
Deadline
Nov 1, 2026
Country
Netherlands
University
Eindhoven University of Technology

How do I apply for this?
Sign in for free to reveal details, requirements, and source links.
Apply for this position
Keywords
Suggested positions
About this position
PhD-TA in Statistics at Eindhoven University of Technology (TU/e), Department of Mathematics and Computer Science, within the Statistics, Probability and Operations Research (SPOR) cluster.
This PhD project focuses on functional data analysis, functional time series, time-varying network structures, and structural change detection. The research aims to develop new statistical methodology and software for analysing complex dynamic data, controlling false connections, and studying dependence structures in non-stationary, non-Euclidean settings. Application areas mentioned include neuroscience, anomaly detection, process monitoring, weather and climate forecasting, and statistical bioinformatics.
The candidate will be supervised by Lujia Bai and Prof. dr. Jeanine Duistermaat. The role includes publishing in international journals, attending international conferences, and building an independent research profile.
Eligibility highlights: a master’s degree in Statistics, Mathematics, Econometrics, or a related field; strong affinity for mathematical statistics and rigorous proofs; fluent English at C1 level; good programming skills in R or Python; C++ experience is a plus; and prior knowledge of time series analysis, functional data analysis, or functional analysis is beneficial. The post also expects motivation to develop teaching skills and coach students.
Funding and conditions: full-time employment for five years, with an intermediate assessment after nine months. Salary is on Dutch university scale P (€3,204–€4,051 gross per month full-time), plus holiday allowance and year-end bonus. Additional benefits include pension, leave, training, commuting/work-from-home support, and international staff support.
How to apply: submit the application online via the vacancy page. Include a cover letter, CV with publications, and contact details for three references. Applications sent by email or post will not be processed. The vacancy remains open until filled.
Location: Eindhoven, Netherlands.
Funding details
Full-time PhD employment for five years with an intermediate assessment after nine months. Salary is on scale P, approximately €3,204 to €4,051 gross per month for full-time work, plus an 8% holiday allowance and an 8.3% year-end bonus. Benefits include pension contributions, leave, training, commuting/work-from-home/internet allowances, and support for international candidates.
What's required
A master’s degree in Statistics, Mathematics, Econometrics or a related field is required. The candidate should be fluent in spoken and written English at C1 level, have good programming skills preferably in R or Python, and experience with C++ is beneficial. Prior knowledge of time series analysis, functional data analysis, or functional analysis is an advantage. The post also values motivation to develop teaching skills, coach students, and strong communication skills.
How to apply
Apply online via the apply button on the vacancy page. Submit a cover letter, CV with publications, and contact details for three references. Do not send applications by email or post.
More information can be found here
Ask ApplyKite AI

How do I apply for this?
Sign in for free to reveal details, requirements, and source links.