The Medical University of Vienna is Europe’s largest medical school and one of the oldest in the world. It was founded in 1365 as the medical faculty of the University of Vienna, and it operates as an autonomous university since 2004. Physicians at the Medical University treat ~95,000 patients per year as inpatients and ~500,000 as outpatients, creating major opportunities for data-driven research. The Medical University has a dedicated data science department (CeMSIIS), with research in statistics, medical informatics, complexity sciences, and other areas. In this department, the Institute of Artificial Intelligence (AI Institute) seeks to advance biomedical research and clinical practice through methods development, applications, and teaching in machine learning and artificial intelligence. The AI Institute is directed by Christoph Bock (https://tinyurl.com/chrbock), who is Professor of [Bio]Medical Informatics at the Medical University of Vienna and Principal Investigator at the CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences. He is a member of the Human Cell Atlas, fellow of ELLIS, and recipient of important research awards (Otto Hahn Medal, ERC Starting Grant, ERC Consolidator Grant, Overton Prize, Erwin Schrödinger Prize). The AI Institute currently hosts two additional group leaders and their research groups: Georg Dorffner (https://tinyurl.com/gdorffner), who is the vice president of the Austrian Society for Artificial Intelligence, and Matthias Samwald (https://tinyurl.com/samwald), who coordinates a major EU project that implements computational methods in clinical practice. Moreover, the Medical University comprises a rapidly growing cluster of machine learning researchers in areas spanning radiology, dermatology, bioinformatics, and synthetic biology.
Machine learning is transforming medicine, for example enabling physicians to incorporate vast amounts of data and knowledge into each of their clinical decisions. Machine learning also advances our understanding of the biology that underlies human diseases, with the future perspectives of identifying the key molecular mechanisms in each individual patient and devising personalized therapies. Researchers at the Medical University of Vienna, together with the CeMM Research Center for Molecular Medicine and the Austrian Academy of Sciences, are working to establish an ambitious research program focusing on “Machine Learning in [Bio]Medicine”, with three pillars: (i) methodological research in machine learning, e.g., focusing on interpretable deep learning, causal modeling, federated machine learning, and/or time series analysis; (ii) proof-of-concept applications in biology and medicine, including personalized medicine and systems biology; (iii) dissemination and impact through sustainable clinical applications, contribution to international consortia, creation of startup companies, and a commitment to research-centric teaching and public outreach. The successful candidate will contribute creatively and proactively to one or more of these directions.
We are recruiting an ambitious PhD student who wants to pursue a scientific career in machine learning, with applications in precision medicine, high-throughput biology, synthetic biology, or cell therapy. The successful candidate will be based at the Institute of Artificial Intelligence at the Medical University of Vienna, with ample opportunities to integrate into the national and European research landscape, including the European Lab for Learning and Intelligent Systems (ELLIS). This call is open to students who are about to finish or recently finished their undergraduate degree in any field of computational sciences, as well as to candidates with a background in biology/medicine and strong quantitative skills.
We are looking for candidates who want to pursue cutting-edge research in the wider field of “Machine Learning in [Bio]Medicine”. A typical background would be a Bachelor and/or Master in machine learning, computer science, statistics, bioinformatics or in another quantitative field, ideally combining methodologically and applied research (in any field). We are also open to candidates with a background in biology, medicine, or a related field if they have strong quantitative skills and a keen interest to engage in machine learning research. The position is fully funded for four years and includes ample opportunities for advancing a scientific career, developing academic leadership skills, engaging in international collaborations, and contributing to the advancement of biology/medicine through computational research. Through the ELLIS network and other consortia, there is also the option to pursue a research stay abroad in a leading machine learning lab with complementary expertise.
Please send your application to firstname.lastname@example.org. The application e-mail should include a cover letter, CV, and academic transcripts, ideally combined into a single PDF document. Any application received by 5 November 2022 will be considered. Start dates are very flexible.