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Field
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HPC environments Good communication skills to interact with collaborators ranging from machine learning researchers to pathologists or medical students Knowledge of biology and medicine is a plus Highly
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: Sucessfully completed scientific university degree (Master) in the fields of chemical engineering, process engineering, chemistry or a comparable discipline Knowledge of hydrogen and energy research is an
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/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages
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networks using common Python-ML libraries such as PyTorch preferably also background knowledge in computational mechanics and applied mathematics highly proficient in spoken and written English We offer you
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, Regional Science, Economic/Quantitative Geography, or Mathematics knowledge and experience in spatial equilibrium modeling (e.g., through coursework, thesis work, or previous projects) is beneficial
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Your Job: The overarching goal is to implement a code for multiscale quantum mechanics / molecular mechanics (QM/MM) molecular dynamics simulations using a Quantum Centric Supercomputing (QSC
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to participate in international meetings Experience with conducting and documenting scientific experiments as well as processing and analyzing data (Python, Origin, Excel) Good communication in English, knowledge
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With its work, the Leibniz Institute of Vegetable and Ornamental Crops (IGZ) contributes to a better understanding of plant systems and thus to the development of sustainable and resilient
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, experimental physics or a comparable discipline Experience in instrumental analytical chemistry Knowledge of hydrogen and energy research is an advantage Experience in the practical application of GC-MS methods
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Description With its work, the Leibniz Institute of Vegetable and Ornamental Crops (IGZ) contributes to a better understanding of plant systems and thus to the development of sustainable and