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Institution Faculty of Biology - Evolutionary Biology
Remuneration group TV-L E13
Full-time / Part-time Full-time (100%)
Start date 01.10.2026 (initially limited to 3 years with possibility to extend)
We are recruiting a postdoctoral scientist to join our international research team in Munich. Whether you are completing your PhD or finishing a first postdoc, this fully funded, long-term position offers a great opportunity to make an impact in evolutionary genetic research and establish a career in science.
The Wolf lab is located at LMU Munich and Max-Planck Institute of Biological Intelligence (MPI-BI) and maintains close ties to a growing evolutionary genetics community representing the breadth of the field (EvoGenMunich). With the Leibniz Supercomputing Centre (LRZ) and its local partners, we have access to state-of-the art computing facilities. Through our EES Master's program and our partnership with the MEME program, we are fortunate to attract exceptional talent, giving you the unique opportunity to work alongside passionate, enthusiastic students from around the world. Munich is Bavaria’s capital combining living traditions with a relaxed, high-quality lifestyle. If you enjoy the outdoors, the Alps and many lakes are just a short train or bike ride away.
We are looking for you:
in Munich
Research in the lab combines evolutionary theory with field work, lab work and large-scale computational approaches to investigate fundamental evolutionary processes in natural and experimental populations (e.g. 1–3). A central goal is to understand the evolutionary processes and molecular mechanisms involved in adaptation and speciation. We integrate diverse sequence-based datasets (WGS, ATAC-seq, RNA-seq, WGBS, EM-seq) from ancient and modern samples with quantitative phenotypes, which we have begun characterizing using AI-based approaches. Study systems range from yeast to whales with primary focus on vertebrates and current emphasis on avian host–parasite systems such as cuckoos and indigobirds (4, 5). The successful candidate is expected to contribute to the lab’s ongoing research and will have creative freedom to develop complementary research directions aligned with the broader goals of the lab.
We are seeking a highly motivated, creative and skilled scientist with a strong background in evolutionary genetics and a passion for understanding the mechanisms that generate biological diversity. The successful candidate has expertise in evolutionary genetic theory and demonstrated proficiency in population genomic, comparative and large-scale -omics data analyses. They will develop and apply innovative computational approaches to existing data sets and will contribute to the design and development of future research directions. Beyond research, the candidate will take an active role in maintaining the lab’s computational infrastructure and contribute to teaching in BSc and MSc courses aligned with the lab’s expertise and research profile (~4 hours per week during the semester).
1. J. W. Poelstra et al., Science. 344, 1410–1414 (2014), 2. C. R. Peart et al., Nat. Ecol. Evol. 4, 1095–1104 (2020), 3. S. Tusso, B. P. S. Nieuwenhuis, B. Weissensteiner, S. Immler, J. B. W. Wolf, Nat. Ecol. Evol. 5, 338–349 (2021), 4. J. Merondun et al., Sci. Adv. 10, eadl5255 (2024), 5. J. Merondun et al., Science. 390, 527–532 (2025)
Applicants holding a PhD with a proven publication record in a relevant field are encouraged to apply.
Also possible in a part-time capacity.
People with disabilities who are equally as qualified as other applicants will receive preferential treatment.
Applications including a statement of motivation, a CV and the contact details of at least two references should be sent as a single .pdf file to [email protected] subject term ‘EvoGen postdoc’ until the 09.07.2026.
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In the course of your application for an open position at Ludwig-Maximilians-Universität (LMU) München, you will be required to submit personal information. Please be sure to refer to our LMU Privacy Policy. By submitting your application, you confirm that you have read and understood our data protection guidelines and privacy policy and that you agree to your data being processed in accordance with the selection process.
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