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assessment, programming and machine learning. If so, we encourage you to apply! You will develop exposure and physical vulnerability maps for past and future (1970-2100) and integrate these into a flood risk
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modeling and networked biological systems. You will work at the intersection of high-performance computing (HPC), computational biophysics, and machine learning, leveraging leadership-class computing
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appropriate care of the equipment • A strong desire for growth, allowing for quick learning and active seeking of feedback • An ability to work well in a team Preferred Qualifications: • Previous experience
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first comprehensive liberal arts and research campus in the Middle East to be operated abroad by a major American research university. Times Higher Education ranks NYU among the top 30 universities in
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | 21 days ago
that provides equal opportunities. We are convinced that diverse teams and a variety of perspectives enrich our work and our daily collaboration. In a continuous process of learning and reflection, we aim
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, including e-mail address and phone number; Statement by the candidate that he/she will not receive remuneration from other projects funded by the National Science Centre; Declaration that the candidate will
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for the analysis of hyperspectral imaging data applied to pictorial layers, based on coupling physical radiative transfer models (two-flux and four-flux approaches) with machine learning methods. The researcher will
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that combines modern machine learning approaches with large-scale biological data to automate genome curation by detecting, interpreting, and correcting structural errors, reducing manual effort from weeks
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· Generous annual and sick leave, life insurance – Faculty Benefits · E. L. Wiegand Fitness Center offers annual or semester memberships and spouse/domestic partner membership options. E.L. Wiegand
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to be 10 million by the year 2050 if new approaches are not undertaken. By joining forces in artificial intelligence (AI), machine learning (ML), chemistry and molecular biology, we intend to develop new