PhD scholarship in computational modelling of protein and nutrient bioavailability of microbial f...

Doctorat / PhD Type de contrat : ["FULL_TIME","TEMPORARY"] Date limite de candidature : 2026-11-30T00:00:00.000Z

Are you fascinated by how the food we eat shapes our microbiome and metabolic health? Excited by the prospect of determining how nutritious are microbial foods? Eager to work in a cutting-edge, interdisciplinary research environment tackling major food-system challenges? Then join us as our new PhD Student in computational modelling of protein and nutrient bioavailability of microbial foods! This position sits within BRIGHT’s Microbial Foods mission. You will help developing computational tools to predict the nutritional value of alternative proteins and nutrients. Our goal is to predict how well a protein or microbial food is digested, absorbed and assimilated in humans, so that foodstuffs can be tailored for a nutritious and sustainable diet without compromising taste and texture. You will build the computational model at the heart of our mission, combining protein language model embeddings with nutritional composition, proteomics and metabolomics data into a multi-modal AI/ML system that predicts digestibility and bioavailability of proteins as well as the bioavailability of micronutrients and food-derived bioactives. The position is fully computational, and you will work with a talented team of scientists generating the in vitro and clinical data that will train and validate your model. Responsibilities and qualifications Responsibilities: Review the state-of-the-art in protein bioavailability, covering digestion, absorption and assimilation, with a focus on microbial foods Build a multi-modal AI/ML model that predicts protein digestibility and bioavailability, combining protein language model embeddings with nutritional composition data and benchmarking against DIAAS and ileal digestibility datasets Create and curate a database of selected microbial foods, for example, Yarrowia lipolytica and Aspergillus spp . Model proteolytic digestion and the absorption of peptides and amino acids and small molecules including transporter-mediated uptake Test and refine the model against proteomics and metabolomics data for single microbial proteins and whole microbial cells Retrain the model with in vitro digestion data and with clinical trial data generated by our experimental partners Apply the model to the computational redesign of microbial foods for improved bioavailability, and release it as an open-source tool Report your research results in peer-reviewed scientific publications and international conferences Collaborate within BRIGHT as well as our local, national and international networks Disseminate your results through scientific publications, public engagement and social media Teach and supervise MSc and BSc students Qualifications: MSc in bioinformatics, computational biology, machine learning, computer science, food science or a related area Advanced programming experience in Python Experience with machine learning, including…