University of Copenhagen
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Postdoctoral Position in Functional Ancient Microbial Ecogenomics at the University of Copenhagen University of Copenhagen in Denmark
Degree Level
Postdoc
Field of study
Computer Science
Funding
Three two-year postdoctoral positions; salary and terms follow the University of Copenhagen/Ministry of Finance agreement for academics in the state. Opportunity to negotiate supplements based on qualifications. No stipend amount is stated.
Deadline
Sep 27, 2026
Country
Denmark
University
University of Copenhagen

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About this position
University of Copenhagen (Globe Institute, Section for GeoGenetics) is advertising three two-year postdoctoral positions in functional ancient microbial ecogenomics within the Ancient Environmental Genomics Initiative for Sustainability (AEGIS).
The positions sit in the Microbial EcoGenomics Group and focus on analysing large-scale ancient environmental DNA (aeDNA) and ancient metagenomics datasets to understand how microbial functions changed across time and space. The three research directions are: computational ancient metabolomics and natural products, carbohydrate-active enzymes (CAZymes) and carbohydrate metabolism, and protein language models for functional annotation of ancient metagenomes.
Research themes include microbial ecology, bioinformatics, computational biology, genomics, evolutionary biology, ecology, and statistical/computational method development. The project works with geological sediments, bones, fossils, and contemporary material from many locations worldwide, aiming to reconstruct past microbial ecosystems and their functional potential.
Eligibility highlights: a PhD in bioinformatics, genomics, community ecology, computational biology, computational metabolomics, or a related field; experience with ancient/degraded DNA and large-scale ancient metagenomic analysis; and strong English communication skills. Depending on the track, experience with machine learning for protein sequences, natural product bioinformatics, biosynthetic gene clusters, CAZyme annotation, or HPC/R/Python is desirable.
Funding and terms: fixed-term postdoctoral employment for 2 years. Salary and employment conditions follow the University of Copenhagen and Danish state academic agreement; supplements may be negotiated. No specific stipend amount is listed.
Application deadline: 27 September 2026, 11:59 pm CET. Apply online with a motivation letter, CV, PhD and MSc certificates (or supervisor statement if the PhD is not completed), and a publication list.
Funding details
Three two-year postdoctoral positions; salary and terms follow the University of Copenhagen/Ministry of Finance agreement for academics in the state. Opportunity to negotiate supplements based on qualifications. No stipend amount is stated.
What's required
Applicants must have a PhD in bioinformatics, genomics, community ecology, computational biology, computational metabolomics, or a related field. Required experience includes analysing large-scale ancient metagenomic datasets, investigating microbial genes/metabolic pathways/functional traits/community-level processes in ecological or evolutionary contexts, and working with ancient or degraded DNA including authentication and low-abundance fragmented sequence data. For the protein language model role, experience implementing and evaluating machine learning models for protein sequences is required. Excellent English, strong analytical skills, teamwork, and interdisciplinary interest are expected. Desirable: computational metabolomics, natural product bioinformatics, biosynthetic gene cluster analysis, CAZyme annotation, microbial carbohydrate metabolism, protein function prediction, R/Python, HPC, strong publication record, and startup/innovation experience.
How to apply
Apply online in English via the university application portal. Include a one-page motivation letter stating the research area, a CV, certified/signed PhD and MSc certificates (or supervisor statement if PhD not completed), and a publication list. Submit before the deadline.
More information can be found here
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