Chalmers University of Technology

Chalmers University of Technology focuses on research and education in technology, natural science, architecture and maritime engineering, and has a strong cross-disciplinary research and innovation section for food and nutrition. It also has a large involvement in health and life-sciences. The Department of Biology and Biological Engineering links top research in systems medicine/biology, food and nutrition, biotechnology with drug discovery, diagnostics and treatment to research and health care. Chalmers is the base for several large scale national and international projects in computational biology, bioinformatics, metabolomics and Artificial Intelligence (AI).

Role in LongITools

Chalmers is involved in research activities in work package 4, supporting the generation of metabolomics data from Generation R, EDEN and PANIC. It will have a lead function in identifying metabolomic and multiomic profiles that reflect exposures in pregnancy and early life.  Metabolomics is a key molecular technique in Chalmers research group on food/diet and health. They have extensive experience of pre-processing and data analysis from smaller scale intervention up to large scale molecular epidemiology. Chalmers will perform these functions in the project using a combination of predictive machine learning, multiomics data fusion and epidemiological modelling.

Professor Rikard Landberg

Principal Investigator (PI)

Rikard is a Professor in Food and Nutrition Science and leads the Division of Food and Nutrition Science at Chalmers. He is an expert in exposure biomarkers, nutritional metabolomics and personalised nutrition. He is PI of large molecular phenotype projects and of several RCTs to evaluate novel personalised nutrition concepts and health effects of plant-based diets. Rikard is a member of the Young Academy of Sweden as well as the National Committee for Nutrition and Food Science at the Swedish Royal Academy of Sciences. He has the overall responsibility of Chalmers activities in LongITools in close collaboration with co-PI, Carl.

Associate Professor Carl Brunius


Carl is an Associate Professor of Computational Metabolomics and an expert in bioinformatics, especially in predictive modelling using machine learning. He develops statistical and machine learning tools that are used to identify metabolomic, proteomic and microbiota profiles associated with dietary exposures and other phenotypic traits. He is involved in Swedish and European projects linking the exposome to health and disease. His role in LongITools is to identify metabolomic and multiomic profiles associated with the different exposure categories.