Postdoctoral Research Fellow (Epidemiologist) (m/f/d)

Postdoctoral Research Fellow (Epidemiologist) (m/f/d) (1073)

Institution: Department für Frauen- und Kindermedizin, Klinik und Poliklinik für Kinder- und Jugendmedizin

• Type of employment: fixed-term for 24 month
• Working hours: full-time / part-time (40,00h)

Start date

Remuneration: TV-L 13

About us – the Medical Faculty

The Medical Faculty of Leipzig University, with its tradition spanning more than 600 years, is one of the largest research institutions in the Leipzig region.

With over 1,300 employees, it is the largest of the university's 14 faculties and serves as a training center for approximately 3,500 students in human medicine, dentistry, pharmacy, and midwifery.

We are seeking a highly motivated Epidemiologist to design and conduct epidemiological research in pediatric populations, focusing on the determinants of child health, the development of common childhood diseases, particularly obesity, and the prevention and long‑term outcomes of childhood obesity and metabolic diseases.

The research group “Childhood Obesity and Metabolic Research”, led by Antje Körner, investigates the development, mechanisms and health consequences of childhood obesity.

The translational approach combines experimental research, clinical studies and genetic approaches.

Our international and interdisciplinary team is closely integrated with the research structures of the Medical Faculty of Leipzig University, Helmholtz Munich, and leading local as well as national research consortia, such as the Excellence cluster Lei Ce M, the German Center for Child and Youth Health (DZKJ), and our large children’s and adolescents’ cohort LIFE Child.

We have large, well-characterized cohorts up and running with a longitudinal setting and across the entire age range: LIFE Child (n~6000), Leipzig Obesity Childhood Cohort (n~2500), and Leipzig Adipose Tissue Childhood cohort (n~700), with deep phenotyping allowing for combining clinical, epidemiological, lifestyle and functional omics and multi‑omics data.

Key Responsibilities

• Design, plan, and conduct epidemiological research projects, including cohort and intervention studies.
• Develop study protocols and statistical analysis plans.
• Analyze and interpret complex population‑based, clinical, and/or health‑related datasets.
• Preparation of scientific manuscripts, reports, presentations, and grant applications.
• Ensure high standards of data quality, reproducibility, and compliance with ethical and data protection regulations.
• Present research findings at national and international conferences and scientific meetings.
• Provide methodological expertise and consultation to ongoing research projects; collaborate closely with clinicians, statisticians, bioinformaticians, and other researchers
• Supervision junior researchers or students.
• Required Qualifications

Education

Candidates should have a Ph. D. and/or M. D. degree in: Epidemiology, Public Health, Biostatistics, Medicine, Health Sciences or a related discipline.

• Professional Experience
• Experience in the design and implementation of epidemiological studies, large cohort studies.
• Experience working with large-scale health, clinical, or population-based datasets.
• Strong understanding of epidemiological study designs and methodologies.
• Experience with observational and interventional research.
• Experience in data cleaning, validation, and quality assurance.
• Familiarity with evidence-based medicine and public health principles.
• Track record of scientific publications in peer-reviewed journals is desirable.
• Experience in interdisciplinary and collaborative research environments.
• Knowledge of research ethics and data protection requirements.
• Experience in grant writing is an advantage.
• Knowledge of causal inference methods (e. g., Target Trial Emulation, Mendelian Randomization) is desirable.
• Statistical and Analytical Skills
• Proficiency in at least one statistical programming language such as: R, SAS, Stata, Python.

• Experience with general statistical methods

• Regression modeling
• Longitudinal data analysis
• Missing data methods
• Sensitivity analyses
• Knowledge of modern analytical approaches, including machine learning methods, is an advantage.
• Personal Competencies
• Strong analytical and problem‑solving skills.
• Excellent organizational and project management abilities.
• Ability to work independently and collaboratively in multidisciplinary teams.
• Communication skills: English – excellent; German – very good

Candidates with one or more of the following areas of expertise are particularly encouraged to apply:

• Cohort studies
• Precision medicine and risk prediction modeling
• Multi-omics, biomarker, or biobank data integration
• Obesity, diabetes, cardiovascular disease, or metabolic health research

What we offer

• a modern workplace and attractive working conditions (mobile working)
• flexible working hours and a good work–life balance
• a discounted public transport ticket (MDV Job Ticket)
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