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Marek Mutwil
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PhD fellowship in AI-driven knowledge graphs and network models of plant stress responses University of Copenhagen in Denmark
Degree Level
PhD
Field of study
Computer Science
Funding
PhD fellowship financed by the Novo Nordisk Foundation through the Ascending Investigator grant NNF26OC0113093; full-time position for up to 3 years.
Deadline
Jan 31, 2027
Country
Denmark
University
University of Copenhagen
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About this position
The PhD fellowship is based in the Mutwil group at the Department of Plant and Environmental Sciences (PLEN), University of Copenhagen, working at the interface of comparative and evolutionary plant biology and AI-driven discovery. The project focuses on computational plant biology and aims to turn the plant literature and multi-omics data into evidence-backed predictions of gene function and stress regulation, with particular attention to heat and drought resilience in Nordic crops.
The student will build on the group’s existing resource PlantConnectome and develop a successor knowledge graph that can integrate information from more than 200,000 open-access plant articles. The work combines large language models, knowledge graphs, graph-based reasoning, and discrete network models to extract entities, relationships, and supporting evidence; build provenance-aware networks; and generate testable predictions about gene function and stress signalling.
This is a computational project, but it is embedded in a broader experimental research environment. The group also generates single-cell stress data and validates predictions in rapeseed, so the student’s computational models will be connected to real biological testing. The research setting includes modern molecular biology laboratories, plant growth facilities, and dedicated high-performance computing and GPU resources.
The group is part of a dynamic and international environment on the Frederiksberg Campus in Copenhagen and maintains a portfolio of community resources under the .plant.tools domain, including PlantConnectome, CoNekt, diurnal.plant.tools, and evorepro.plant.tools. The position is supervised by Associate Professor Marek Mutwil.
Funding details
PhD fellowship financed by the Novo Nordisk Foundation through the Ascending Investigator grant NNF26OC0113093; full-time position for up to 3 years.
What's required
Applicants must have completed a degree equivalent to a Danish master’s degree (180 ECTS BSc + 120 ECTS MSc) in a relevant field such as bioinformatics, computational biology, computer science, physics, mathematics, molecular biology, or a related discipline. A strong quantitative interest is required. Experience with natural language processing, large language models, graph databases, network modelling, or machine learning is an advantage. Programming experience (e.g. Python) is an advantage, but not required at entry. Strong analytical reasoning and scientific judgment are valued, as is an interest in plant biology. Good written and spoken English is required.
How to apply
Apply electronically via the APPLY NOW link and submit all attachments in English. Include a one-page motivation letter, written answers to the four application questions, CV, diplomas/transcripts, and publication list/reference letters if available. Ensure the application is complete and submitted before 31 January 2027 at 23:59 GMT+1.
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Professors
Associate Professor at University of Copenhagen
Denmark
Research Interests
Statistics
Artificial Intelligence
Biology
Computer Science
Environmental Science
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