232 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" positions at Nature Careers in United States
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on bioinformatics, computational biology, machine learning, Ai, and/or related fields, from applicants committed to translational research applicable to the field of cancer. The DCCB, located at the Health Science
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driven, to allow researchers to focus on data intensive tasks. What we provide: An opportunity to broaden research experience in a collaborative environment. A team that believes in continuous learning and
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collaborative environment. A team that believes in continuous learning and cultivates an environment of collaboration. Collaboration with research labs and other shared resources, including Molecular Genomics
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collaborative environment. A team that believes in continuous learning and cultivates an environment of collaboration. Once trained, flexible schedule What you’ll do: Operate equipment in the cagewash facility
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machine learning techniques, will quantify groundwater recharge and groundwater resilience. Your responsibilities: Analyse the dynamics of hydrological connectivity of soil moisture using gridded soil
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uncertainty? What motivates our mice to solve this difficult problem? How does the brain support flexible behavior and strategy-switching? Learn more about the Dennis lab here What we provide: A collaborative
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machine learning methods are a plus. Qualifications: PhD in neuroscience, or related fields DeepLabCut or similar methods Demonstrated hands-on experience with 2-photon imaging techniques Experience
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) and brings together expertise in protein engineering, advanced microscopy, and machine learning. Our goal is to develop a protein biosensor optimization pipeline that integrates high-throughput
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continue until the position is filled. Principle Responsibilities: The successful candidate will teach anatomy & physiology or histology courses, introductory biology courses, and offer versatility in
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Pathology and Neuropathology). In this position, you will be a key member of our interdisciplinary team, working closely with image scientists, machine learning researchers, and clinical collaborators