Doctoral Student (m/f/x) with a background in Statistics and Data Science

Faculty of Mathematics, Informatics and Statistics - Statistical consulting unit (StaBLab), LMU, and Genetic Epidemiology, University of Regensburg
Start date
as soon as possible
Application deadline
1 May 2021
Remuneration group
TV-L E 13
Contract duration
a full-time position for three years

In the StaBLab, we develop and apply statistical methods and software that help solve real data problems. The StaBLab has a particular focus on methods development for misclassification problems and model mis-specification in association analyses. Here, we seek to help interpret genetic data for common, complex diseases. Genome-wide association studies are one of the most successful approaches to identify and characterize the genetics of common diseases and to help prioritize drug targets for prevention and intervention. The GenEpi at Regensburg, haslarge data from meta-analyses of international consortia on kidney function decline and age-related macular degeneration. Both diseases lack effective therapy. We develop statistical methods including software approaches to tackle methodological challenges, like gene x environment interaction, misclassification and mis-specification of the statistical model, as well as aspects specific to progression phenotypes.

The StaBLab, Munich has a long-standing cooperation with the GenEpi, Regensburg, and a strong track record to support our junior scientists. Our research work is funded by the BMBF, the DFG, and the National Institutes of Health, USA. This position can be hold in Munich or Regensburg with a commitment to visit the respective second group on a regular basis.


  • a master in statistics or data science or related field
  • strong statistical background
  • ability to work independently on statistical problems and data analyses
  • proficiency in R
  • interest in genetics, epidemiology, and big data analysis
  • excellent English (spoken and written)
  • interest in medical research questions and interdisciplinary work.


  • A stimulating research environment across two strong research facilities with the opportunity to work in local and international research groups
  • An interdisciplinary team including statisticians, mathematicians, biologists, computer scientists, and clinicians
  • Expert supervision for both statistics and the applied field
  • A strong track record in supporting and training our young team members, and
  • An opportunity for doctoral work including lead author publications and conference presentations.

Also possible in a part-time capacity.

People with disabilities who are equally as qualified as other applicants will receive preferential treatment.


Please submit your application including motivation letter, CV, copy of university graduation, copy of high school diploma (Abitur) to Prof. Dr. Helmut Küchenhoff until May, 1st.

Prof. Dr. Helmut Küchenhoff, LMU München
Prof. Dr. Iris Heid, University of Regensburg


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