76 parallel-processing-bioinformatics PhD positions at Technical University of Munich in Germany
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processing and machine learning methods, and big data analytics solutions to extract highly accurate large-scale geo-information from big Earth observation data. Our team aims at tackling societal grand
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. However, how insects perceive, discriminate, and process the biological information encoded in CHC profiles remains poorly understood. PhD Position: The PhD candidate will investigate the chemoreception
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PhD Position in Theoretical Algorithms or Graph and Network Visualization - Promotionsstelle (m/w/d)
. The group’s work in this area has led to best paper awards at PacificVis and Graph Drawing, with recent publications in IEEE Transactions on Visualization and Computer Graphics and Computer Graphics Forum
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research experience and are explicitly encouraged (e.g. South America, Asia or Africa). The PhD process will be accompanied by integration into TUM’s School of Life Sciences or School of Management and
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Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. (data protection information on collecting and processing personal data
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are unfortunately unable to return your application documents once the procedure has been completed. As part of your application for a position at the Technical University of Munich (TUM), you will be submitting per
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control software and machine learning expert. How you will support us: ▪ You will take on responsibilities in the field of control and operation of high-coherence superconducting quantum circuits, with a
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Your profile: • University degree (MSc or PhD) in any of physics, engineering, medicine or biology. • Experience in optics and signal processing that allows a quick adaption to the technological needs
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the objectives more precise; working on the individual PhD study project with its focus on the methodological contributions as well as on empirical data processing for the case study analysis in collaboration with
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Materials” concentrates on the understanding of structure-performance indicators in electrocatalytic reactions. Our catalysts are the heart of sustainable energy conversion processes such as in hydrogen fuel