Machine Learning in BioMedicine (ERC-funded postdoc position)

Organization
CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences
Job Location
Vienna
Austria
Job Description

The successful candidate will develop and apply advanced machine learning technology (e.g., deep neural networks, kernel methods, non-linear regression, and/or causal modeling) in order to discover fundamental mechanisms of biology and medicine and to advance personalized medicine. Potential applications may include (but are not limited to) single-cell sequencing of cancer, 3D reconstruction of tumors and epigenetic landscapes, mobile health technology for patients with brain cancer, and pattern discovery in heterogeneous biomedical datasets. Our location on one of the largest medical campuses in Europe ensures direct relevance to medicine, while our close collaboration with the Max Planck Institute for Informatics (Germany) provides first-hand access to a cutting-edge computer science environment.

Requirements

We are looking for highly motivated and academically outstanding candidates who want to pursue a career in machine learning research and its applications in biology and medicine. Candidate should have a strong background in the quantitative sciences (computer science, bioinformatics, statistics, mathematics physics, engineering, etc.). We will also consider applicants with a background in medicine or in biology (e.g., functional genomics, chemical biology, human genetics, molecular medicine, etc.) who have strong quantitative skills and a keen interest in pursuing computational projects with a major machine learning component.

How to Apply

Please apply online (https://cemm.jobbase.io/job/2ikdvm1m) with cover letter, CV, academic transcripts, and contact details of three referees. Applications will be reviewed on a rolling basis. Any application received by 31 August 2017 will be considered. Start dates are very flexible.

About Our Organization

The Institute (http://www.cemm.at/)

CeMM is an international research institute of the Austrian Academy of Sciences and a founding member of EU-LIFE. It has an outstanding track record of top-notch science (last five years: >10 papers in Nature/Cell/Science/NEJM, >25 papers in Nature/Cell sister journals) and medical translation. With just over a hundred researchers, CeMM provides a truly collaborative and personal environment, while maintaining critical mass and all relevant technologies. Research at CeMM focuses on cancer, inflammation, and immune disorders. CeMM is located at the center of one of the largest medical campuses in Europe, within walking distance of Vienna’s historical city center. A study by “The Scientist” placed CeMM among the top-5 best places to work in academia world-wide (http://the-scientist.com/2012/08/01/best-places-to-work-academia-2012). Vienna is frequently ranked the world’s best city to live. It is a United Nations city with a large English-speaking community. The official language at CeMM is English, and more than 40 different nationalities are represented at the institute. We are convinced that diversity and a multicultural work environment are clear advantages for successful research and are committed to attract, develop, and advance the most talented individuals regardless of their gender, sexual orientation, religion, age, disability status or any other dimension of diversity.


The Lab (http://epigenomics.cemm.oeaw.ac.at/)

The Medical Epigenomics Lab at CeMM pursues an interdisciplinary and highly collaborative research program aimed at understanding the cancer epigenome and establishing its utility for precision medicine. The lab is internationally well-connected and active in several fields:

  • Epigenomics. Many diseases show widespread deregulation of epigenetic cell states. As members of the International Human Epigenome Consortium, we use epigenome sequencing to dissect the epigenetic basis of cancer and immune disorders.
  • Technology. Groundbreaking biomedical research is often driven by new technologies. Our lab is therefore heavily invested into technology development, including single-cell sequencing, CRISPR screens, and epigenome editing.
  • Bioinformatics. New algorithms and advanced computational methods allow us to infer epigenetic cell states from large datasets, in order to reconstruct the epigenetic landscape of cellular differentiation and complex diseases.
  • Diagnostics. New technologies (genome sequencing, mobile devices, etc.) provide important information for personalized medicine. We develop and validate assays and algorithms for translating the value of digital medicine into routine clinical practice.


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