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skills. Excellent programming skills in Python and Julia with experience with deep learning frameworks (e.g., PyTorch, TensorFlow). Experience building complex software systems, preferably with industry
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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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researchers in pursuit of advancing knowledge and making significant contributions to their respective fields. ESSENTIAL QUALIFICATIONS/EXPERIENCES PhD Graduation; Strong background in deep learning, machine
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, Division of Applied Mathematical Science (Team Director; Eiryo Kawakami) (5) Medical Science Deep Learning Team , Division of Applied Mathematical Science (Team Director; Jun Seita) (6) Prediction
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multidisciplinary team comprised of fellow postdoctoral appointees, experimentalists, and staff scientists, with computational fluid dynamics (CFD) and artificial intelligence/machine learning (AI/ML) expertise, with
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Computation and Adaptation , RIKEN Center for Brain Science (Laboratory Head: Taro Toyoizumi) Medical Data Deep Learning Team , Advanced Data Science Project , RIKEN Information R&D and Strategy Headquarters
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SIT's mission is centred on nurturing industry-ready graduates who possess deep technical expertise and transferable skills to address future challenges. We collaborate with industry in our
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SIT's mission is centred on nurturing industry-ready graduates who possess deep technical expertise and transferable skills to address future challenges. We collaborate with industry in our
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following areas: 1) statistical genetics/genomics/omics, or 2) deep learning/AI. Most importantly, we value candidates who demonstrate both the ability and drive to rapidly learn and implement recent advances
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in one or more of the following areas: computational biology/bioinformatics, biomedical informatics, deep learning/machine learning, data mining, biostatistics, or a closely related area. Proficiency