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organoids will be plus. Dry lab: Highly motivated candidates with a PhD/MD degree in bioinformatics, genome science, systems biology, biomedical informatics, computational biology, machine learning, data
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to candidates from a broad range of AI subfields, including, but not limited to machine learning, generative AI, computer vision, representation and reasoning, natural language processing
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the broad landscape of computational science, including artificial intelligence, machine learning, deep learning, and their applications in addressing complex scientific and societal challenges, encompassing
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Nature Careers | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | 1 day ago
Health and the IWK Health Centre in Halifax. The successful candidate will have an opportunity to be part of the Big Data Analytics, AI & Machine Learning research cluster in Computer Science, and the
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in high-performance computing, materials chemistry, theoretical chemistry, molecular dynamics, data science, and machine learning are beneficial. What we offer: We offer a position with a competitive
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in image processing, quantitative analysis, and biological interpretation Proficiency in AI/machine learning tools for image segmentation, transformation, registration, or tracking Solid mathematical
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particular NLP, statistical learning, machine learning, generative AI, and their major fields of application. Roles and responsibilities The applicant will join the team of the 3IA Côte d’Azur Institute and
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microscopy images or recorded animal behavior to apply. Such information will aid analysis of experimental data or help establish automated image processing/machine learning pipelines. Technicians will
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programme at the Faculty of Science . The ideal candidate has a background in or experience with one or more of the following topics: SIMD performance engineering. Machine Learning. Communication-efficient
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computational modeling and/or analysis of complex biological systems, integrating state of the art tools such as machine and deep learning approaches. Experience in managing biological databases and statistical