172 computer-programmer-"https:"-"Inserm"-"FEMTO-ST" "https:" "https:" "https:" "CNRS" positions at Leibniz
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, computer science, medicine, pharmacology, and physics. ISAS is a member of the Leibniz Association and is publicly funded by the Federal Republic of Germany and its federal states. In the department
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, computer science, medicine, pharmacology, and physics. ISAS is a member of the Leibniz Association and is publicly funded by the Federal Republic of Germany and its federal states. In the department
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, computer science, medicine, pharmacology, and physics. ISAS is a member of the Leibniz Association and is publicly funded by the Federal Republic of Germany and its federal states. In the department
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, computer science, medicine, pharmacology, and physics. ISAS is a member of the Leibniz Association and is publicly funded by the Federal Republic of Germany and its federal states. In the department
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as well as through peer-reviewed publications Our requirements: Completed university degree in the field of engineering, physics, computer sciences or mathematics Experience in the field of plasma
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cooperate with the University of Rostock and are an integral part of the teaching program of the Institute of Physics. Our network includes the research community worldwide. As an institute of the Leibniz
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, and maintain research code; prepare documentation and reports. Your qualifications Enrolled student (MSc or advanced BSc) in computer science, data science, physics, engineering, mathematics, or a
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) and related to the major multi-national initiative “GOE-DEEP” supported by the International Continental Scientific Drilling Program (ICDP) and aiming to study the climate at the time of the first rise
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Instrumentation’ group pursues an ambitious programme in the field of optical spectroscopy and develops stateof-the-art multi-object, integral-field and high-resolution spectrographs for observatories worldwide
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Leibniz Institute of Plant Biochemistry (IPB) in Halle (Saale), Germany, where we are offering a fully-funded PhD position within the DFG Priority Programme SPP2363: “Molecular Machine Learning”. About the