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University of Copenhagen
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Postdoctoral Position in Computational Multimodal Data Integration for Crop Stress Regulatory Networks University of Copenhagen in Denmark
Degree Level
Postdoc
Field of study
Computer Science
Funding
The three-year fixed-term postdoctoral position is financed by the Novo Nordisk Foundation through the Ascending Investigator grant "Accelerating crop resilience with AI-enabled gene function prediction and stress regulatory networks." Employment and salary follow the Danish academic staff agreement with the Ministry of Taxation and the Danish Confederation of Professional Associations; salary supplement negotiation is possible. No specific stipend or tuition information is stated.
Deadline
Jan 31, 2027
Country
Denmark
University
University of Copenhagen
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About this position
The University of Copenhagen’s Department of Plant and Environmental Sciences invites applications for a postdoctoral position in computational biology within the Mutwil group. The project focuses on using multimodal single-cell and epigenomic data to resolve gene regulatory networks underlying crop responses to heat and drought.
The research covers four Nordic crops—rapeseed, potato, wheat and barley—and examines stress responses across multiple organs, time points and conditions. The postdoctoral researcher will serve as the computational integrator of a grant investigating climate-driven crop resilience, transforming sequencing and literature-derived data into interpretable regulatory networks.
The work begins with single-cell RNA-seq and ATAC-seq data generated on a 10x Genomics platform. Responsibilities include developing quality-control and integration pipelines, handling doublets and ambient RNA, annotating cell types using conserved markers, and creating reproducible workflows that can be extended by PhD students.
A major research component is the inference of transcription factor–target relationships and the identification of cis-regulatory elements through known motifs, de novo motif discovery, convolutional neural networks and DNA language models. These elements will be connected into TF–CRE–target triplets, benchmarked against established frameworks such as SCENIC+ and MAESTRO, and ranked according to conservation across the four crop species.
The postdoc will also connect regulatory networks with the group’s literature-derived knowledge graph, gene-function predictions and open web resources, supporting the prioritization of regulators and targets for validation in rapeseed. The role includes co-supervising PhD and master’s students and helping expand the group’s single-cell and multi-omics analysis capacity.
The Mutwil group works at the intersection of comparative and evolutionary plant biology and AI-driven biological discovery. The postdoctoral researcher will collaborate with the group’s researchers and with Prof. Ryan Lister at the University of Western Australia and Prof. Zoran Nikoloski at the University of Potsdam. The position is based at the Frederiksberg Campus in Copenhagen, with access to substantial computational resources, including GPU resources through LUMI and uCloud.
Funding details
The three-year fixed-term postdoctoral position is financed by the Novo Nordisk Foundation through the Ascending Investigator grant "Accelerating crop resilience with AI-enabled gene function prediction and stress regulatory networks." Employment and salary follow the Danish academic staff agreement with the Ministry of Taxation and the Danish Confederation of Professional Associations; salary supplement negotiation is possible. No specific stipend or tuition information is stated.
What's required
Applicants must hold a PhD, or have submitted their thesis by the start date, in bioinformatics, computational biology, genomics, plant molecular biology or a related field. Applicants need documented experience analyzing single-cell RNA-seq, single-cell ATAC-seq or comparable multimodal genomic data; strong Python or R programming skills; experience building reproducible workflows using tools such as Snakemake or Nextflow, version control and containers; a publication record demonstrating independent scientific contribution; and excellent written and spoken English. Advantageous experience includes gene regulatory network inference, motif analysis, cis-regulatory element prediction, deep-learning models of regulatory sequence, graph-based methods, comparative or cross-species transcriptomics, plant abiotic stress biology, crop species and co-supervision of students.
How to apply
Submit the application electronically through the APPLY NOW portal at https://go.talentech.io/avwnz. Include an English motivation letter, CV, diplomas, publication list, up to three relevant papers, a research statement, and contact details for two or three references.
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Professors
Associate Professor at University of Copenhagen
Denmark
Research Interests
Statistics
Artificial Intelligence
Biology
Computer Science
Omics
Professor
Denmark
Research Interests
Comparative Genomics
Computer Science
Computational Biology
Agriculture
Single-cell Analysis
Professor
Denmark
Research Interests
Agriculture
Single-cell Analysis
Biology
Computer Science
Comparative Genomics
ApplyKite TwinLearns as you applyMake your next move.
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