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)! Tübingen has a long history of academic excellence (founded in 1477; DNA was discovered here ; linked to 11 Nobel laureates) and is an innovation center in medicine and machine learning. About Eberhard
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Tübingen offers a combination of high-performance medicine and strong research. The goal of the Carl-Zeiss-Project “Certification and Foundations of Safe Machine Learning Systems in Healthcare” is to enable
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in machine learning, AI and programming skills, e.g. Python basic knowledge of materials science / materials engineering Leibniz-IWT is a certified family-friendly research institute and actively
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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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, nationality, ethnicity, sexual identity, physical abilities, religion or age. Qualified applicants with physical disabilities will be given preference. Learn more about diversity at Helmholtz Munich Our
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protein biochemistry, single particle cryo-EM or cryo-ET is an asset, curiosity and willingness to learn new methods and adjust to technological developments a must. Strong written and oral
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projects and deadlines Scientific track record Fluency in English; German proficiency or the willingness to learn is advantageous Familiarity with data-analysis / scripting tools (e.g. SCiLS Lab, METASPACE
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, initiative/commitment, ability to work in a team and willingness to cooperate, willingness to learn We offer: Interdisciplinary research at the interface of politics, economics and society Work in national and
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reduction, uncertainty quantification, machine learning, fluid mechanics. Experience with scientific object-oriented programming languages (C++, Python, or Julia) is highly relevant. Knowledge
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timings) affect the metabolome and proteome of rapeseed seeds. Your findings will serve as molecular fingerprints to support Deep Learning models for hybrid development. Whom we are looking for: An early