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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | about 1 month ago
holography. We are seeking a highly motivated postdoctor-al researcher to join our multidisciplinary team at the intersection of optics, electronics, machine learning, and atmospheric science. The successful
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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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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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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 17 days ago
learning. It also offers the opportunity to work with data from the European XFEL facility at DESY. Project website Your profile Eligible candidates have strong skills in computational physics and
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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
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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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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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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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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