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Max Planck Institute for Evolutionary Biology, Plön | Plon, Schleswig Holstein | Germany | 26 days ago
on several available Drosophila panels. In a parallel evolve and re-sequence (E&R) project, Drosophila populations will be experimentally evolved for larger/smaller embryo size. The postdoc will be responsible
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Profile: A Master`s degree and an excellent PhD degree in Biochemistry, Chemistry, or a related Molecular Science Proven Track Record in Machine Learning, Molecular Simulations, Chemoinformatics
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Your Job: The PhD project offered will be part of the Cluster of Excellence: PhenoRob - Robotics and Phenotyping for Sustainable Crop Production. PhenoRob performs world-leading research in robotics
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-edge Machine Learning applications on the Exascale computer JUPITER. Your work will include: Developing, implementing, and refining ML techniques suited for the largest scale Parallelizing model training
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, transcriptomic, and proteomic approaches. In parallel, engineered Aspergillus niger strains will be developed for the sustainable production of selected pigments as dyes, which will be further scaled up
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advanced imaging. The successful candidate will have the opportunity to develop and lead their own independent research project and build a small research team by hiring PhD students and postdocs. In
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comprised of a variety of W3 University professors along with their postdocs and PhDs. You will contribute to SFB1574 - the Circular Factory, which explores how future production systems can seamlessly
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Infrastructure? No Offer Description Work group: IBG-3 - Agrosphäre Area of research: PHD Thesis Job description: Your Job: The PhD project offered will be part of the Cluster of Excellence: PhenoRob - Robotics
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, chromatin profiling, and advanced imaging. The successful candidate will have the opportunity to develop and lead their own independent research project and build a small research team by hiring PhD students
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on the Exascale computer JUPITER. Your work will include: Developing, implementing, and refining ML techniques suited for the largest scale Parallelizing model training and optimizing the execution User support in