PhD Student Position: Machine Learning in Biology & Medicine
|Published||February 11, 2023|
Machine learning is transforming medicine, for example by 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, in partnership with the CeMM Research Center for Molecular Medicine and the Austrian Academy of Sciences, are building an ambitious research program focusing on Machine Learning in Biology & Medicine, with three pillars: (i) methodological research in machine learning, for example focusing on interpretable deep learning, causal modeling, federated machine learning, or time series analysis; (ii) proof-of-concept applications in biomedical research, 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 researchcentric teaching and public outreach. The successful candidate will contribute creatively and proactively to one or more of these directions
We are seeking individuals who are interested in pursuing cutting-edge research in the wider field of Machine Learning in [Bio]Medicine. Candidates should have a Bachelor and/or Master degree in machine learning, computer science, statistics, bioinformatics or in another quantitative field that combines both methodological and applied research (in any field). Candidates with a background in biology, medicine, or a related field are also eligible if they possess strong quantitative skills and a keen interest in machine learning research. This fully funded fouryear PhD position offers ample opportunities to kickstart a scientific career, develop academic leadership skills, engage in international collaborations, and contribute to the advancement of biology/medicine through computational research. Additionally, through the ELLIS network and other consortia, there is the option to spend part of the PhD abroad in a collaborating machine learning lab with complementary expertise.
A full PDF version of this job posting is available from the following URL: https://www.medical-epigenomics.org/files/PhD_Student_Machine_Learning_in_Medicine_Jan_2023.pdf.
Please send your application to email@example.com (ideally as a single PDF document). The application materials should include a cover letter, CV, academic transcripts, and contact details of 2-3 references (if possible). The deadline is 31 March 2023. Start dates are flexible.