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activities. Your Profile: Master and PhD degree in astronomy, physics, computer science or equivalent fields of study. Proven experience in N-body simulations and the comparison of simulation and observation
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reports Develop and apply software tools Document software and data according to the FAIR data principles Contribute to workshops and training activities Your Profile: Master with subsequent PhD degree in
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scattering experiments Conduct and disseminate world-class research via publications and conference presentations Represent and actively work on increasing the user base at MLZ Your Profile: A Master and PhD
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PostDoc in "Geopolitical dilemmas for management: transfer of governance for the Southern Ocean" ...
Integrative Postdoc Pool) is 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
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PostDoc in "Sustaining the keystone: Rethinking Antarctic krill fishery management under climate ...
Integrative Postdoc Pool) is 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
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Institute for Medical Research, and the German Cancer Research Center (DKFZ). Strong interactions exist via the Health + Life Science Alliance Heidelberg Mannheim with the European Molecular Biology
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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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area: Natural products, especially of bacterial origin, are an important source of new antibiotics. These metabolites further play significant roles in microbial interactions and communication
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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
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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