Assistant Professor in Health Data Science (40% time)

at  Syddansk Universitet

The Unit of Genome Biology Research, Department of Molecular Medicine, invites applications for a 3-year position as an assistant professor (40% time) in Health Data Science , specifically within Genomics-based biomarker discovery for diagnostics, and therapeutic and prognostic applications. The position has the possibility of being extended by one year. The position is to be filled as soon as possible.
We seek individuals who have research expertise that complements existing focus areas of the department.
Major research areas of the Genome Biology Research unit are to apply high-end data-driven research for a deeper understanding of gene regulation in development and disease and reveal new biomarkers for diagnosis, prognosis and therapy. To attain these goals, the laboratory is specially interested in integrating cutting-edge multiomics methodologies with bioinformatics and machine-learning techniques.

QUALIFICATIONS

The successful candidate must hold a PhD in Bioinformatics, Biotechnology, Computer Science, Physics, Engineering, Bio-engineering, or equivalent area and must have at least 3 years of postdoctoral training in above mentioned data-driven research areas.
The successful candidate must have demonstrated significant research experience through publications in the relevant area. Special consideration will be given to candidates demonstrating a strong background in analyzing above mentioned single-cell and spatial omics datasets using high-end bioinformatics and machine-learning methods and publishing work in respected peer-reviewed scientific journals.

The main task of the candidate will be to establish lines of data-driven research that strengthen translational and integrative approaches at the molecular and mechanistic levels in the study of development and diseases within our department.
The candidate will employ computational pipelines to analyze complex omics datasets derived from developmental and disease models. Specifically, the candidate will analyze single-cell MultiOmics (scATAC-seq, scRNA-seq), Spatial transcriptome, bulk RNA-seq, ATAC-seq, ChIP-seq, GWAS, fastGRO, CUT&Tag, CUT&Run datasets, and identify more potent biomarkers having translation potential for diagnostics, therapeutic and prognostic applications.
The candidate will also apply machine learning-based techniques on the above single-cell and bulk Omics data sets for stratifying distinct patient populations.
Close collaborations will be expected within the research unit and the Department of Molecular Medicine, as well as with the Department of Molecular Biology and Biochemistry, SDU, and research units within the Department of Clinical Research and Odense University Hospital (OUH). Establishment of strong international collaborations of benefit to the department will be expected as well.