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ability to work in an interdisciplinary manner Creativity and a strong spirit of discovery to develop new research approaches Experience in planning and conducting experimental studies Very good data
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annual bonus and 30 days' vacation per year subsidy for a company ticket for public transport or the Germany Ticket Further information about the can be found on the Internet at www.igzev.de
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of machine learning and health sciences, with unique access to experimental and clinical data. Embedded in Munich’s thriving AI landscape, fellows benefit from world-class facilities, interdisciplinary
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the team of Prof. Dr. Loriana Pelizzon on data and methods for supervision of climate and ESG risks in Capital Markets (incl. investment funds, bonds, stocks). The role involves advising and
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for data-efficient exploration and optimization within the process parameter space as well as for adaptive, data-driven machine learning to map the electrolysis process to a digital twin. Data workflows and
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will perform live-cell imaging experiments and analyze data You will collaborate with other members of the team in advance microscopy and super-resolution techniques You will develop leadership skills
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at Heidelberg University and Stanford University. The group works on a wide variety of research, with foci being medication effectiveness, health services research, and population health issues. One key data
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range of health, prevention and sports offers Contact & Application For further information please contact Prof. Dr. Ralf Gilsbach via e-mail. Interested? Applications will be accepted until 31.07.2025
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motivated PhD students, interns, and PostDocs at the intersection of computer vision and machine learning. The positions are fully-funded with payments and benefits according to German public service
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) is an advantage Experience in software tools such as Origin, Matlab, Python/Matplotlib or similar programs for data processing and evaluation. Knowledge of a relevant programming language complements