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Stellenbeschreibung

Kennziffer: S533105

Statistical Genomics PhD Student, or Postdoc (m/w/d)

Hasso Plattner Institute (HPI) is Germany’s center of excellence for digital engineering (www.hpi.de). The Digital Engineering Faculty, founded jointly by the University of Potsdam and HPI, offers a highly practical and engineering-oriented computer science study program, which is unique throughout Germany.

HPI’s university research earns international recognition, with the main focus of its teaching and research on the foundations and applications of large, highly complex and networked IT systems.

In the course of our ongoing expansion, we are currently seeking a Research Assistant, PhD Student, Postdoctoral Research Scientist or Analyst (m/w/d) in Digital Health with emphasis on Personalized Medicine and Genomics for our location in Potsdam at the HPI Digital Health Center (www.hpi.de/digital-health-center) with option to be partly based in New York City at the newly formed HPI Digital Health at Mount Sinai (See Press Release for more details).

Your future role encompasses:
* Creative research to gain insights in ways to improve personalized medicine.
* Opportunity to work on interdisciplinary, national and international research projects, for example together with HPI Digital Health Center at Mount Sinai using data from the Mount Sinai Data Warehouse and BioMe Biobank.
* Publication of scientific findings in peer-reviewed research journals.
* Support communication of knowledge, within research and teaching.

Scientific research topics may include, but are not limited to:
* Clinical Informatics: Working with electronic health record (EHR) data, applying cutting edge methods to describe the data and derive novel phenotypes.
* Statistical Genomics: Genome-wide association studies using directly genotyped, sequenced or imputed data as well as EHR-derived phenotypes, analysis of multiple phenotypes, fine-mapping of association signals, polygenic risk scores, genetic correlation, Mendelian randomization.
* Machine Learning: Data mining, applying supervised and unsupervised methods, e.g. for modelling of clinical endpoints based on free text, imaging data, or time series data.

Qualifications:
* Master’s degree or PhD in areas such as bioinformatics, biostatistics, statistical genomics, computer/data sciences, machine learning or deep learning, physics, mathematics, or equivalent degrees in medicine and advanced health sciences.
* Excellent skills in high-level programming languages and frameworks (e.g. python, R, SQL) is required.
* Excellent communication and presentation skills, including a good knowledge of English.
* We expect the candidate to be motivated, goal-oriented, creative, communicative and happy to work in a collaborative and inter-disciplinary environment with high interest in self-improvement.

What we offer...
* Set in an international and state-of-the-art working environment, we offer you a multi-faceted job in which you contribute directly to the institute’s success.
* You work in a dynamic enterprise—on a unique interface between private and public higher education, with future-looking flexibility and financial stability.
* We have flat hierarchies, a motivated team and an unbureaucratic approach.
* Your workplace, on the beautiful HPI campus, offers the best transportation connections to Berlin.