216 image-processing-and-machine-learning-"RMIT-University" Postdoctoral positions in Germany
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, enrichment analyses - biological interpretation of data Your qualification - PhD/MSc degree in bioinformatics, computer science, mathematics, life sciences - background in Machine Learning and/or RNAseq
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Max Planck Institute for the Structure and Dynamics of Matter, Hamburg | Hamburg, Hamburg | Germany | about 1 month ago
Strong Coupling”), funded by a prestigious Synergy Grant from the European Research Council (ERC), investigates how quantum electrodynamics can be harnessed to control chemical and physical processes
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Graduiertenkolleg "Temporalities of Future" Prof. Dr. Stefan Rinke Rüdesheimer Str. 54-56 14197 Berlin (Wilmersdorf) With an electronic application, you acknowledge that FU Berlin saves and processes your data. FU
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information on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm
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to supervise PhD, Master and Dr. med (thesis as part of medical studies in Germany) students. The fellow will also have the opportunity to teach as part of the institute’s Masters and doctoral program but will
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to teach as part of the institute’s Masters and doctoral program but will not be required or expected to do so. The salary is paid according to the German TV-L system (the salary agreement for public service
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reliability of R-Mode, particularly under varying environmental conditions. Key objectives include understanding the physical processes that affect R-Mode signal propagation, quantifying the variability
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qualification in an internationally oriented research institute. Your main tasks will include: Independent development and processing of research questions in the field of conversation analysis regarding
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computer aided methods. Qualifications and Experience • Outstanding academic degree in materials science, metallurgy, metal physics or similar degree • Excellent doctorate with focus on computational
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projects in basic biomedical research and who wish to learn methods relevant to their current research. To this end, the grant finances the participation in practical training courses or short-term research