You will build your own research programmes in fields relevant to exposome research that will leverage the extensive study populations, biological samples, and genetic/genomic data available within the Utrecht Exposome Hub. The new faculty will develop collaborations with existing faculties who have expertise in epidemiology, sociology, geosciences, data sciences, metabolomics, microbiomics, statistics, bioinformatics, and system biology and medicine. Successful candidates will engage in teaching students and post-doctoral fellows. Academic appointment as Assistant or Associate Professor rank at the UMCU/UU will be commensurate with the applicant's experience.
We are looking for a highly motivated and creative research scientist (Assistant Professor) who will contribute to the development and implementation of new bioinformatics and biostatistics tools and methods that are needed for high-quality exposome research both now and in the future. The successful candidate will exhibit interest and experience in bringing solutions to real-world data projects, requiring a fine balance between a pragmatic and a more critical attitude. Experience with machine-learning approaches, network models, and causal effect models is a plus but not strictly required.