Two PhD Fellowships in AI-Driven Discovery of Plant Metabolic Pathways University of Copenhagen in Denmark

The University of Copenhagen invites applications for two PhD fellowships in AI-driven discovery of plant metabolic pathways, hosted by the Department of Plant and Environmental Sciences at Frederiksberg Campus. The positions are doctoral candidates DC7 and DC8 in the Marie Skłodowska-Curie Doctoral Network Stripes&Stars, which investigates modern breeding of ornamental and fruit crops through flower and fruit colour and specialized metabolites, including anthocyanins and other flavonoids in petunia, calibrachoa, poinsettia and bilberry.

DC7: Knowledge graph construction for specialized-metabolite pathways

This project will make fragmented scientific knowledge about plant metabolism computable. The doctoral researcher will use the PlantConnectome large-language-model pipeline to extract information from more than 70,000 publications and connect enzymes, substrates, transporters, transcription factors, stresses and genetic modifications in a comprehensive knowledge graph. The work will extend the graph to environmental contexts, apply symbolic reasoning and graph neural networks to infer missing pathway components, and develop an interactive interface for evidence-linked information on genes, pathways and phenotypes.

DC8: Multi-omics co-expression networks for predicting novel metabolic pathways

This project will systematically identify genes involved in plant pigment and specialized-metabolite production. The researcher will build condition-specific co-expression and regulatory networks from consortium and public RNA-seq data using the TEA-GCN algorithm, integrate cell- and tissue-resolved expression with proteomic and epigenomic datasets, and combine network evidence with the DC7 knowledge graph. Neurosymbolic reasoning and graph machine learning will be used to prioritize enzymes, regulators and environmental cues for experimental validation.

Both doctoral researchers will work closely with experimental partners and contribute to a shared computational framework for predictive colour and specialized-metabolite engineering. DC7 includes secondments at TU Wien and Klemm + Sohn, while DC8 includes a secondment at the University of Amsterdam. Both projects include network-wide schools, workshops and transferable-skills training.

The Mutwil group, led by Associate Professor Marek Mutwil, works at the interface of comparative and evolutionary plant biology and AI-driven biological discovery. The international group develops cross-species gene-expression atlases, comparative co-expression networks and knowledge graphs, supported by molecular biology facilities, plant-growth facilities and high-performance computing and GPU resources.