Qualifications

We are searching for a self-driven scientist who works well in interdisciplinary teams. The ideal candidate holds a Ph.D. in human genetics, statistical genetics, bioinformatics or other related fields, with at least a few years of relevant industry or postdoctoral experience.

Familiarity with high performance computing and cloud-based computing environments is a plus. A strong interest in AI methods, and experience with machine learning techniques applied to genomics data is highly desired.

You should have:

Familiarity with databases that house genomics data (including but not limited to UK Biobank, All of Us, Genomics England, gnomAD, TOPmed). Hands on experience is strongly preferred Strong knowledge of genetics, genomics, and interest in the application of AI techniques in these fields Proven track record by publications in peer-reviewed journals and/or conference presentations Proficiency in programming languages, for analysis of large-scale datasets, e.g., R, Python, or similar, as well as experience with bioinformatics tools and databases Have experience of communicating insights and presenting complex scientific concepts to a diverse audience.

Preferred experience includes:

Experience with population stratification, Mendelian randomization, polygenic risk score (PRS) analysis, and/or gene-environment interaction analysis is strongly preferred Understanding of multi-omics data (transcriptomic, proteomic, epigenomic etc.). Hands on experience is strongly preferred Experience with biomarker discovery

As a person, you have a good team ethic, pay close attention to detail, and enjoy a fast paced, dynamic environment where creative intellectual independence and knowledge sharing is actively encouraged. Most importantly, you must have a strong interest in applying your skills in the field of drug development.

About the Department

You will be a member of our Translational Genomics and Precision Medicine Department which is part of the Human Genetics CoE. The focus of the CoE is to use data science and human genetics to discover and develop new drug targets and biomarkers through a range of human centric approaches e.g., high-through put genetic discovery screens; Mendelian randomization; pLoF variant screens and precision medicine approaches relevant to type 2 diabetes, chronic 

kidney disease, CVD, non-alcoholic steatohepatitis (NASH), obesity and rare endocrine and blood disorders.

The CoE is anchored in the recently established Digital Science & Innovation (DSI) organisation within Research & Early Development at Novo Nordisk. DSI is supporting the digital journey across all our therapy areas in R&ED. In DSI, we work in multidisciplinary teams in strong collaboration with all areas across R&ED and R&ED IT. We participate in drug development projects across the value chain, from early discovery to pre-clinical development. We engage in external collaborations to ensure access to the latest research and technology enablers, and we automate our labs and processes, and we focus on developing and retaining top talent.