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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | about 1 month ago
biology, (bio-)chemistry, and biophysics and have great interest in interdisciplinary research with an eagerness to learn and develop new approaches. Candidates should hold a Masters or equivalent degree in
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Simulations (LES). The analysis will be performed together with teams at the Helmholtz-Zentrum Hereon that focus on ocean turbulence and machine learning as a part of the TRR181 Collaborative Research Centre
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At the Leibniz Institute of Plant Biochemistry in the Department of Bioorganic Chemistry a position is available for a PhD in Machine Learning for Enzyme Design (m/f/d) (Salary group E13 TV-L, part
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Description At the Leibniz Institute of Plant Biochemistry in the Department of Bioorganic Chemistry a position is available for a PhD in Machine Learning for Enzyme Design (m/f/d) (Salary group E13
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. This includes research on psychological assessment, psychometrics, and methods in large-scale assessments. Your tasks We are seeking an international visiting researcher to collaborate on an innovative research
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specimen-based analysis of trace fossils with exploratory fieldwork in southern Namibia, and neoichnological experiments in collaboration with scientists at Senckenberg am Meer in Wilhelmshaven. With
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-based metadata platform that you will help develop. In collaboration with stakeholders from energy research, you will develop methods to increase data and software interoperability, enabling the automated
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collaboration with Q.ANT GmbH in Stuttgart, a deep-tech company that develops photonic computing and photonic sensing products. The goal of this project is the development of highly integrated vapor cells with
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systems on different temporal and spatial scales. For our Research Group Applied Optimization we are looking for a PhD student: New Deep Learning - based Framework for Energy Modelling: Combination
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to contact Prof. Dr. Paolo Panza by e-mail (Paolo.Panza[at]uni-giessen.de) Our offer to you Integration into an innovative research project Interdisciplinary collaboration with excellent scientists Opportunity