Postdoctoral Scholar – Personalized Medicine and Data Science applied to Pulmonary Hypertension (PH) – DTU – Lyngby

The Novo Nordisk Foundation, Center for Biosustainability, is seeking a highly motivated, independent, and collaborative postdoctoral research scholar interested in personalized medicine and pulmonary hypertension. This position will be responsible for the development and application of graph-based knowledge mining techniques.Developing targeted treatments and personalized diagnostic strategies requires an understanding of biological processes, the molecules (DNA, RNA, protein, small molecules) involved in them and their interactions. Such knowledge is spread over several public information silos and scientific publications. The goal is to create a unified knowledge graph and perform knowledge mining to extract mechanistic relationships. This position will participate in the further development of an existing open-source knowledge mining software platform called Lifelike; customize it for personalized medicine by incorporating additional human health related pathway databases and perform knowledge mining applied to the research of Pulmonary hypertension. Pulmonary hypertension (PH) is a progressive, life-threatening, incurable disease. The pathological mechanisms underlying PH remain elusive. Our group introduced a novel approach for studying PH endothelial function, building on the genome-scale metabolic reconstruction of the endothelial cell (EC) to investigate intracellular metabolism. This approach revealed that the intracellular metabolic activities of ECs in PH patients cluster into four phenotypes independent of the PH diagnosis and that disease severity differs significantly between the metabolic phenotypes, suggesting their clinical relevance. Hereby, a novel avenue for true precision medicine becomes possible by deciphering the pathophysiology of the different PH metabolic phenotypes using Genome-scale metabolic models (GEMs) constrained with multi-omic data and by applying graph-based knowledge mining approaches against an integrated knowledge graph. This position will work closely with Professor Pär Ingemar Johansson at the Rigshospitalet, the Quantitative Modeling of Cell Metabolism Group at the Center for Biosustainability and the Principal Investigator and team for Lifelike development. Responsibilities and qualifications Perform knowledge mining related to PH research; analyze omics data by contextualizing it against integrated knowledge. Generate knowledge maps and present results with storyboards.  Write code to load new data sources and perform testing to ensure data integrity. Utilize existing scripts to extract relationships from literature and populate the integrated knowledge graph. Work with the development team on developing data models for new knowledge sources. Candidates must have a PhD in the Biological Sciences field.  Curiosity and passion for elucidating biological mechanisms and attention to detail. Excellent presentation skills and ability to explain complex analysis clearly to different stakeholders. Coding experience in Python. Excellent written and verbal communication skills and ability to work in a cross-functional team. Experience with data loading, database design or SQL query language is a plus. Prior experience with graph algorithms preferred but this job presents an opportunity to learn this skill. We offerDTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility. Salary and terms of employment The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. Initial appointment will be for one year.

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