Connectionists: PhD position: Machine Learning in [Bio]Medicine, Medical University of Vienna

[Georg Dorffner]

PhD Student: Machine Learning in [Bio]Medicine

Medical University of Vienna
Institut für Artificial Intelligence
Vienna, Austria

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.

The Goal

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.

Please send your application to sec-ai at meduniwien.ac.at. 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.
Desired skills and experience

The Candidate

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.

The Host Institution

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.