Biostatistician (m/w/d)

What You’ll Do - Data Quality & Statistical Validation

Perform the scientific acceptance of datasets from our laboratory: content-level quality control, plausibility checks, biological validity and fitness for purpose.

Distinguish genuine biological signals from technical and statistical artifacts (e.g., batch or plate effects, confounding study factors) and develop normalization procedures that correct for them.

Critically assess results for robustness - effect sizes, multiple-testing correction, confounders and reproducibility across cohorts - before they are reported.

What You’ll Do - Analysis & Pattern Discovery

Develop and run reproducible analysis workflows on large autoantibody and multi-omic datasets, applying biostatistics and machine learning to uncover patterns and generate new biological insights.

Combine population-based analyses with longitudinal monitoring of individuals to distinguish normal variation from meaningful change in autoantibody profiles over time.

What You’ll Do - Scientific Output & Knowledge Building

Interpret results biologically with our medical research team and translate findings into statistically valid, biologically plausible and understandable results.

Build a knowledge pool of epidemiological autoantibody profiles from our own data, benchmark it against public reference sources, and annotate findings with public protein, epitope and disease databases (e.g., UniProt, IEDB, Open Targets).

PhD or equivalent research experience in bioinformatics, biostatistics, immunology or a related field.

Strong background in and enthusiasm for immunology

In-depth knowledge of autoantibody, proteomics and multi-omic data analysis, and excellent interpretation skills linking results back to the underlying science.

Strong programming skills (e.g., Python, R, SQL or JavaScript) and the willingness to pick up new languages, coding environments and app deployment workflows.

Readiness to work on site in Dortmund - fluent English and German.

Preferred Qualifications

Experience with population-based or epidemiological studies.

Experience running projects with pharmaceutical or biotech partners, contract research customers or grant-funded consortia, from study design to delivering results.

Good overview of medical and biological online resources and databases, and how to use them.

Impact: Your analyses turn raw data into the answe...

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Quelle: Statistisches Bundesamt (Destatis), Tabelle; dl-de/by-2-0; eigene Berechnung