Research Associate / Doctoral Candidate in Environmental Data Science and Epidemiology (m/f/d/x)

Salary Scale 13 TV-L, 29.4 hours/week (Part-time: 75%).
Starting from 1 December 2026 for the duration of 3 years (with the possibility of extension depending upon funding)

Project description:

This interdisciplinary research position bridges environmental epidemiology, geostatistics and data science to develop best-practice data pipelines for environmental data in epidemiologic studies in order to investigate how environmental conditions and exposures influence human health.

The position is part of the collaborative BMFTR project “DataNord” that aims at establishing an interdisciplinary data competence center for the Bremen region. In DataNord, members of the U Bremen Research Alliance which is a cooperative network of the University of Bremen and thirteen non-university research institutes – work together with other regional institutions.

As part of the second phase ofthe DataNord Research Academy, the “Healthy Planet” sub-project will investigate the association of environmental factors, socioeconomic factors and biodiversity with each other and their complex effects on health and health behavior. The project will combine high-resolution environmental exposure data provided by satellite and link them with individual level health-related data of children to examine (amongst others) to what extent children from socially vulnerable households face exposure to air pollution and heat and have access to green or blue spaces. It will also assess environmental and biodiversity data with health indicators to explore how local ecosystems and human health interact.

The position entails a very close cross-departmental collaborations within BIPS, particularly between the Department of Epidemiological Methods and Etiological Research and the Department of Research Data Infrastructures and Data Science.

Tasks:

• Developing data pipelines for spatial data to enrich population-based cohort data with environmental exposures based on publicly available land use and remote sensing data.
• Preparing workflows, maintaining and enriching environmental datasets, and conducting required data science tasks.
• Contributing to statistical analysis of large-scale, longitudinal population-based cohort studies (e.g., the IDEFICS/
  I.Family cohort).
• Preparation of scientific manuscripts for international, peer-reviewed journals and presentation of research findings at scientific conferences.
• Support in the planning, coordination, and administrative management of ongoing and future research projects within the respective research areas.

Requirements:

• Master’s degree (or equivalent) in Environmental Sciences, Data Sciences, Biostatistics, Bioinformatics, Epidemiology, Public/Global Health, Geography, Computer Science, or a related quantitative discipline.
• Knowledge or experience in geospatial data processing and analysis, with a strong interest in applying these methods to environmental exposure data.
• Basic knowledge of epidemiological research methods and the ability to formulate structured research questions.
• Motivation to develop and apply data science methods and workflows in an interdisciplinary research setting.
• Good writing skills, excellent English proficiency (written and spoken), and a demonstrated capacity for collaborative, interdisciplinary teamwork.
   

Desirable Qualifications and Skills:

• Operational knowledge in geographical information systems (GIS) and programming skills in statistical software (R, python) are highly advantageous.
• Track record of peer-reviewed scientific publications.
• Previous experience analyzing epidemiological data is advantageous.

While the position is primarily aimed at candidates interested in pursuing doctoral research, it is also open to those who wish to develop their research career without pursuing a PhD degree. For interested candidates, a structured PhD program is available in conjunction with the University of Bremen.

What We Offer:

The Leibniz Institute for Prevention Research and Epidemiology – BIPS is one of Germany’s most renowned epidemiological research institutes, aiming to identify the causes of health problems and develop new concepts for disease prevention in close cooperation with national and international partners. We offer an international research environment, a state-of-the-art computing and data infrastructure, institutional links to the academic network of the University of Bremen, and a structured scientific qualification framework. Academic development and scientific qualification are integrated components of this role. For doctoral candidates, BIPS offers a structured PhD program in conjunction with the University of Bremen. 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.

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

Inquiries:

For specific inquiries regarding the position, please contact:
Dr. Rajini Nagrani, Tel: +49-(0)-421 / 218-56842, Email: nagrani(at)leibniz-bips.de
 

Additional information can be found at: bips-institut.de.

Please submit your comprehensive application in PDF format, compiled as a single unified document, quoting reference number A26-26 by October 30, 2026, to:

bewerbung(at)leibniz-bips.de

Please note that applications which do not comply with the required format (1 PDF document) cannot be considered.

For information on salaries, please refer to the TV-L salary calculator for 2026; the position is classified under pay grade E13 of the TV-L. Salary calculator: oeffentlicher-dienst.info/c/t/rechner/tv-l/allg

Leibniz Institute for Prevention Research and Epidemiology – BIPS                      
Human Resources Department
Achterstr. 30
28359 Bremen
Germany