PhD scholarship in computational modelling of protein and nutrient bioavailability of microbial foods Technical University of Denmark in Denmark

PhD scholarship at the Technical University of Denmark (DTU), BRIGHT – The Novo Nordisk Foundation Biotechnology Research Institute for the Green Transition. This fully computational PhD project focuses on modelling the protein and nutrient bioavailability of microbial foods. The position is based in BRIGHT’s Microbial Foods mission and sits at the intersection of food science, computational biology, machine learning, and nutritional systems research.

The successful candidate will develop a multi-modal AI/ML framework to predict how well microbial proteins and foods are digested, absorbed, and assimilated in humans. The model will integrate protein language model embeddings with nutritional composition, proteomics, and metabolomics data to predict protein digestibility, bioavailability of micronutrients, and food-derived bioactives. The project is explicitly computational and will be supported by in vitro and clinical datasets generated by experimental collaborators.

Research tasks include: reviewing the state of the art in protein bioavailability; building a predictive model benchmarked against DIAAS and ileal digestibility datasets; creating and curating a database of microbial foods such as Yarrowia lipolytica and Aspergillus spp.; modelling proteolytic digestion and uptake of peptides, amino acids, and small molecules; testing the model against proteomics and metabolomics data; retraining it on in vitro digestion and clinical trial data; and applying the model to the redesign of microbial foods for improved bioavailability.

The project is embedded in a highly interdisciplinary environment within BRIGHT and its local, national, and international networks. The research team is working on AI-powered design of microbial foods that balance consumer acceptance, health, sustainability, and scalability. The broader mission includes multi-omics characterization, sensory analysis, life-cycle assessment, safety testing, and predictive modelling for flavor, texture, nutrition, and process scale-up.

Eligibility highlights: applicants should hold an MSc in bioinformatics, computational biology, machine learning, computer science, food science, or a related discipline, or an equivalent two-year master's degree (120 ECTS). Strong Python skills, machine learning/deep learning experience (e.g. PyTorch), and excellent English are required. Experience with protein language models, proteomics, metabolomics, nutrition metrics such as DIAAS/PDCAAS, database curation, and open-source development is advantageous.

Funding and duration: the appointment is a 3-year full-time PhD scholarship at DTU under the Danish collective agreement for professional associations. The call notes that the project is not funded by an EU programme.

Application window: applications must be submitted online by 30 November 2026 at 23:59 Danish time. Applicants must submit all materials in one PDF via the DTU recruitment portal, including a motivation letter, CV, transcripts, degree documents, and one reference letter with referee contact details. The preferred start date is 1 April 2027, or earlier by mutual agreement.