PhD in Statistics

Laplace Expert Ltd; Eindhoven; Hybrid; EUR 36,000 - 45,000; Full time

Job summary

Eindhoven University of Technology in the Netherlands is seeking a PhD candidate in statistics to study functional data, time-varying networks and structural changes. The project develops methodology for functional time series and networks, with emphasis on non-Euclidean data structures.

The position is 4 years full-time, with funding of EUR 3204-4051 per month and is based in the SPOR group of the Department of Mathematics and Computer Science.

Qualifications

• MSc in statistics, mathematics, econometrics or a closely related quantitative field is required.
• Background in time-series analysis or functional data analysis is advantageous.
• Strong statistical computing skills with R and Python are expected.

Skills

Time-series analysis

Functional data analysis

Statistical computing

R

Python

C++

Education

MSc in statistics, mathematics, econometrics or related quantitative field

Tools

R

Python

C++

Job description

Eindhoven University of Technology · Department of Mathematics and Computer Science, SPOR group

Netherlands

Apply by 18 Oct 2026

About This Opportunity

Eindhoven University of Technology is recruiting a PhD candidate in statistics to study functional data, time-varying networks and structural changes. Applications close on 18 October 2026 at 23:59 Europe/Amsterdam.

The project develops statistical methodology for functional time series and time-varying networks, including structural changes and non-Euclidean data structures. The work combines statistical theory, computation and software implementation.

statistics functional data time series networks change-point analysis

Level PhD

Time Commitment Full-time

Duration 4 years

Reference Code 2026/583

Field Functional Data Analysis and Time-Varying Networks

Specialization Mathematics

Organization Type University

Funding & Compensation

Amount EUR 3204-4051 / Per Month

Funding Type Salary

Funding Status Paid

Period Per Month

Requirements

Education

Applicants should hold an MSc in statistics, mathematics, econometrics or a closely related quantitative field.

Experience

Background in time-series analysis, functional data analysis or functional analysis is advantageous.

Technical Skills

R Python C++ Functional data analysis Time-series analysis Statistical computing