Diet–Microbiome Data Scientist: Metagenome-to-Food Insights

DTU; Kongens Lyngby; Remote; DKK 600,000 - 800,000; Full time

Job summary

DTU is inviting applications for a PhD-level research role within BRIGHT’s Mission 2: Microbial Foods. The project aims to design AI-driven microbial foods with health, sustainability and scalability goals, focusing on fungal chassis and multi‑omics characterisation.

You will link inferred food intake to microbiome data, work across BRIGHT, and advance predictive models for flavor, nutrition and process scale-up in collaboration with national and international partners.

Qualifications

• Experience with large-scale shotgun metagenomic analysis and taxonomic/functional profiling.
• Strong programming skills in Python and/or R; experience with HPC or cloud environments.
• Solid statistical skills and experience with machine learning.
• Experience with or motivation to learn in vitro/ex vivo fermentation or synthetic community experiments.

Responsibilities

• Develop dietary inference framework linking intake to microbial species, MAGs and pathways.
• Build curated food-reference databases including fermented and plant-based foods.
• Mine large public/collaborative metagenome cohorts for diet–microbe–function associations.
• Apply statistical, compositional, network and ML approaches to identify diet-associated patterns.
• Design and run validation experiments and feed data into BRIGHT’s modelling pipeline.
• Communicate results through publications/presentations.

Skills

Metagenomic analysis

Python

R

Statistics

Machine learning

Diet–microbiome interactions

Collaborative mindset

Education

PhD degree

Tools

HPC

Cloud environments

Job description

DTU is inviting applications for a PhD-level research role within BRIGHT’s Mission 2: Microbial Foods. The project aims to design AI-driven microbial foods with health, sustainability and scalability goals, focusing on fungal chassis and multi‑omics characterisation.

You will link inferred food intake to microbiome data, work across BRIGHT, and advance predictive models for flavor, nutrition and process scale-up in collaboration with national and international partners.