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Max Planck Institute for Radio Astronomy, Bonn | Bonn, Nordrhein Westfalen | Germany | about 5 hours ago
for collaborative research with PhD students, including their supervision and teaching within the MuSES project. Application Process Interested and qualified individuals should submit the following: A curriculum
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also designed to allow networking between (marine) institutions. We therefore offer the possibility for candidates to foster external relationships, or in consultation, to bring in additional advisors
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publications with Peer-Review Your Profile: Completed university masters degree (physics/chemistry) with a PhD Strong knowledge and experimental experience in X-ray photoelectron spectroscopy Suitability to work
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, RNA seq, single cell sequencing, spatial transcriptomics), bioinformatics tools and human studies. Your profile: PhD in bioinformatics, oncology or computational biology profound experience in system
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, complex geometry, arithmetic geometry, algebraic number theory, global analysis, algebraic topology. We have a large group of PhD students, postdocs and visitors here at Essen, and have many joint
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team to work on machine learning-supported rapeseed genomics and breeding. Your tasks: You design, train and interpret deep-learning models to predict regulatory gene variants in rapeseed genomes. You
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preclinical in vitro and in vivo models Supervise and mentor MSc/MD/PhD students Collaborate with national and international research partners Present your results at scientific meetings Publish your findings
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projects of the research group Qualification Required: A diploma and a PhD in microbial natural product chemistry Hands-on experience and a strong understanding of metabolomics/dereplication of natural
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06.12.2021, Wissenschaftliches Personal The professorship of Data Science in Earth Observation is seeking six new PhD candidates/PostDocs for its new center for Machine Learning in Earth Observation
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hearing loss. However, current neural devices are large, complex, and invasive, and are therefore used by only a fraction of people who could benefit from them. The goal of NANeurO is to design new