At Umeå University we are looking to fill the positions for one DDLS fellow in Data-driven precision medicine and diagnostics.
At Umeå University several departments at two faculties have a long standing collaboration and strong research environment in development of diagnostics and molecular medicine. Frontline research is performed using biological markers (from molecular genetics and proteins to tissue and metabolomics), imaging (molecular and structural), clinical/laboratory registry data and finally advanced data analytics, data fusion and computational modeling approaches.
The departments are closely integrated with the University Hospital with the imaging facilities at Radiology and Clinical Physiology and clinical diagnostics on human tissue at Laboratory Medicine. Umeå center for functional brain imaging (UFBI) is an inter-disciplinary research center that works with different imaging techniques to examine the function and structure of the brain in relation to both basic and clinical questions.
Umeå provides an excellent research infrastructure for the fellow with access to large and unique prospective data collections and biobanks such as Biobanken norr, Northern Sweden Health and Disease Study (NSHDS) and the Uppsala-Umeå Comprehensive Cancer Consortium (U-CAN).
The university also serves as a node for Genomic Medicine Sweden (GMC) and the SciLifeLab platform for Clinical Genomics. The experimental laboratory research at the departments are integrated at the Translational Research Centre (TRC) and the Wallenberg Centre for Molecular Medicine (WCMM) is another notable area of strength.
Data-driven precision medicine and diagnostics The subject area concerns data-driven research on precision medicine, such as the use of computational tools to integrate molecular and clinical data for translational research and diagnostic development thereby facilitating individualized patient care. Data integration and analysis can be used for patient stratification, for discovery of diagnostic biomarkers and for longitudinal monitoring and follow-up. Precision medicine also depends on capabilities for data interpretation, visualization and clinical decision support. The research is expected to use assets, such as electronic health care records, molecular data (e.g. imaging and omics), as well as longitudinal patient and population registries, biobanks and digital monitoring data.
