Statistician (Postdoc or PhD candidate) (m/f/d/x)

Freie Hansestadt Bremen; Bremen; On-site; EUR 55,000 - 70,000; Full time

Job summary

The Leibniz Institute for Prevention Research and Epidemiology – BIPS GmbH in Bremen seeks a Statistician (Postdoc or PhD candidate) to develop new statistical methods and apply them to health data. The role includes participation in international research projects and publishing findings.

Candidates should have a Master’s or PhD in statistics, a solid statistical background, and programming skills in R, Python or SAS. Excellent English and a passion for interdisciplinary research are essential.

Qualifications

• Master’s/PhD in statistics or related field.
• Solid background in statistics.
• Programming skills in R, Python or SAS; other languages like C++/Java are beneficial.
• Good command of spoken and written English.
• Strong interdisciplinary research interest.
• Initiative, motivation, commitment and scientific curiosity.

Responsibilities

• Develop new statistical methods and apply them to health data.
• Participate in joint (international) research projects.
• Publish and present research results.
• Develop software packages.
• Co-supervise bachelor and master students (postdocs: co-supervise PhD students).
• Support external funding acquisition and develop independent research projects (postdoc only).

Skills

Statistics

R

Python

SAS

English

Interdisciplinary

Education

Master/PhD in statistics

Tools

C++

Java

Job description

Statistician (Postdoc or PhD candidate) (m/f/d/x)

The Leibniz Institute for Prevention Research and Epidemiology – BIPS develops effective strategies for the prevention of chronic, non-communicable diseases. Supporting a healthy life-course early on is our primary goal. The focus of our research is therefore on factors beyond individual diseases, such as lifestyle and environment, biological and social factors, as well as early detection of diseases and drug safety. Our research spectrum covers methodological development, the identification of the causes of diseases, and intervention and implementation research. We also engage in close dialogue with politicians and the general population and provide academic qualification to young scientists. We offer exciting research topics, a stimulating international environment, a good infrastructure, close ties to the University of Bremen and an engaged, supportive and cooperative team. Postdocs are encouraged to strive for scientific independence and to establish their own research focus.

BIPS holds the audit ‘berufundfamilie’ (work and family) certificate and actively promotes the compatibility of career and individual lifestyle through flexible working hours, mobile working options, and continuous professional development. We also offer additional support for international scholars to relocate to Germany through the Welcome Center of the U Bremen Research Alliance.

EG 13 TV-L

01.01.2027

Statistical Methods in Epidemiology

• Develop new statistical methods and apply them to health data


• Participate in joint (international) research projects


• Publish and present research results


• Develop software packages


• Co-supervise bachelor and master students (postdocs: also co-supervise PhD students)


• Support acquisition of external funding, develop independent research projects (postdoc only)

• Master’s / PhD degree (or equivalent) in (bio-)statistics, (bio-)mathematics, data science, computer science or related disciplines


• Solid background in statistics


• Programming skills in R, Python or SAS; other languages such as C++ or Java are beneficial


• Good command of spoken and written English


• Strong interest in interdisciplinary research


• Initiative, motivation, commitment, and scientific curiosity

A26-25

15.11.2026

Befristet

In the coming years, the Leibniz Institute for Prevention Research and Epidemiology – BIPS will expand its prevention research within the context of large epidemiological cohort studies. In doing so, it will also place a focus on methodological and implementation research. The institute conducts its own studies in this area (e.g., IDEFICS/I.Family cohort study), participates in the NAKO Health Study, and conducts targeted research using secondary data from health insurances. For research to be conducted within the framework of these cross-departmental topics, we are looking for several statisticians with methodological focus in at least one of these topics:

• Causal Inference (CI), e.g., target trial emulation, double-robust estimation methods


• Machine Learning (ML), e.g., interpretable machine learning, (tabular) foundation models


• Statistical analysis of cohort data (SC), e.g., trajectories of health outcomes and their determinants


• Statistical modelling of health behaviors and complex exposures (HB), e.g., from wearable sensors, omics


• Statistical analysis of health insurance data (SH), e.g., survival analysis and quantitative bias analysis

Among equally qualified applicants, preference will be given to severely disabled candidates.