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Markus Stetter

3 months ago

PhD Student in Plant Genomics and Quantitative Genetics – Crop Evolution Group, CEPLAS, University of Cologne University of Cologne in Germany

Degree Level

PhD

Field of study

Evolutionary Biology

Funding

Available

Deadline

Expired

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Country

Germany

University

University of Cologne

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Where to contact

Official Email

Keywords

Evolutionary Biology
Population Genetics
Agriculture
Biology
Computational Biology
Quantitative Genetics
Python
Maize
Bioinformatics
Genomic Analyses
- Plant Genomics
Multiomics Data Analysis
Amaranth
Bash Scripting

About this position

The University of Cologne, one of Europe’s largest and oldest universities, is seeking a motivated PhD student to join the Crop Evolution group at the Institute for Plant Sciences and the Cluster of Excellence on Plant Sciences (CEPLAS). This position focuses on plant genomics and quantitative genetics, with a particular emphasis on the evolution and adaptation of maize. The research group investigates how new traits evolve, the domestication of wild plants into crops, and the global spread of these crops, using advanced population and quantitative genetics approaches.

The successful candidate will engage in funded research projects, conducting genomic analyses to uncover the history of adaptive variation in maize. Responsibilities include population genetic and quantitative genetic analysis, contributing to project development, writing and publishing scientific articles, presenting results at conferences, and participating in group meetings and discussions. The research environment is stimulating and collaborative, offering opportunities to participate in cutting-edge research and benefit from extensive advanced training and occupational health management.

Applicants should possess a Master’s degree in a relevant field such as computational biology, evolutionary genetics, or plant breeding. Essential qualifications include a background in population genetics, quantitative genetics, or computational biology, experience with omics data analysis, and computational skills (bash, R, or Python). Excellent oral and written communication skills in English are required, along with a keen interest in evolutionary questions and plant research.

The position is available immediately and is offered on a part-time basis (65% of full-time), with funding provided according to remuneration group 13 TV-L of the German public sector. The contract is fixed term until 31 December 2028. The University of Cologne is committed to equal opportunities and diversity, welcoming applications from all qualified candidates regardless of gender, nationality, ethnic and social origin, religion, disability, age, sexual orientation, or identity. Women will be considered preferentially in accordance with the Equal Opportunities Act of North Rhine-Westphalia.

To apply, submit your application online via the University of Cologne job portal, including proof of required qualifications and referencing Wiss2511-21. The application deadline is 14 December 2025. For further inquiries, contact Professor Markus Stetter at [email protected]. More information about the research group can be found at www.cropevolution.org.

Funding details

Available

What's required

Applicants must hold a Master’s degree in a relevant field such as computational biology, evolutionary genetics, or plant breeding. A background in population genetics, quantitative genetics, computational biology, or equivalent is required. Candidates should have experience with omics data analysis and computational skills, including knowledge of bash, R, or Python. Excellent oral and written communication skills in English are essential. Interest in evolutionary questions and plant research is expected.

How to apply

Submit your application online via the University of Cologne job portal at https://jobportal.uni-koeln.de/bewerben/2422?lang=en. Include proof of required qualifications and reference number Wiss2511-21. Do not include a photo. For questions, contact Professor Markus Stetter at [email protected].

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