Assistant Professor in Multimodal Bioinformatics

Assistant Professor in Multimodal Bioinformatics

Aalborg University

Basel, Switzerland

Job description

The integration of genotypes with electronic health records have led to the identification of several loci associated to disease risk and drug response. You will be responsible for continuing this research by developing a research group with a special focus on identifying genetic profiles separating individuals at risk of disease from those without risk, as well as responders from non-responders to medical treatments in cancer and cardiovascular diseases. To improve the accuracy of the stratification, the genetic profiles will be included in multimodal machine learning models with e.g. ECGs, images, multi-omics, or registry data. You will work in close collaboration with local, national, and international specialist on integrating the extensive genotyped dataset of the Danish Blood Donor Study, Copenhagen Hospital Biobank, and the Danish Cancer Biobank with data from Danish registers. Your key responsibility will be bioinformatics and machine learning analysis, but you will also take part in the planning of studies, contribute to writing scientific papers as well as acquiring funding.

Furthermore, you will get responsibilities in our collaborative projects with the Department of Haematology, Oncology, and Molecular Diagnostics within analysis of omics-data.

Finally, teaching and supervision duties within bioinformatics and machine learning at the Faculty of Medicine, Aalborg University, may be expected.

Qualification requirements

Appointment as an Assistant Professor presupposes scientific qualifications at PhD–level or similar scientific qualifications in bioinformatics or a related field. The research potential of each applicant will be emphasized in the overall assessment.

You are expected to have:

• Experience with omics and data analysis in a clinical context
• Experience with programming in R or Python, and use of command line tools
• Experience with data management and analysis of large data sets
• A solid publication track record in bioinformatic journals as first or lead author
• A strong motivation for interdisciplinary research
• Excellent writing and communication skills in English with a good scientific vocabulary

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