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Field
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at least a PhD Degree in Epidemiology, Public Health, Environmental Health, Biological Sciences, Biostatistics, Data Science, preferably with relevant experience. Prior experience with machine learning is a
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subject and normally within eight years of completing a PhD or close to submitting a PhD. The ability to foster a respectful working and learning environment and a commitment to equality, diversity and
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needed, and otherwise contribute to overall lab operations. The applicant will be a collaborative, impact-focused problem solver who wants to be part of a dynamic team. Learn more about the innovative work
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for remote sensing and uncertainty estimation. Candidates must have a strong programming background. Requirements: PhD in Computer Science or a related field with a strong emphasis on machine learning
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Inverse Methods and Ionospheric Modelling Research Fellow - School of Engineering - 106995 - Grade 7
to completion) relevant to empirical modelling (any discipline), machine learning (any discipline), inverse methods (any discipline), ionospheric modelling and/or ionospheric measurement techniques, radio
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workflows, and supporting infrastructure, while working closely with behavioral scientists and collaborating with computer scientists and technical teams Play a central role in developing the enterprise model
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scientists, biomedical informaticians, clinicians, and public health researchers to develop deployable, trustworthy methods that improve patient outcomes and health system operations. Key responsibilities
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/Computer Vision. The experience in diffusion models is a plus. Have a PhD degree in computer science/engineering or related disciplines. Knowledge of autonomous vehicles or cyber security will be
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engineered constructs. Learn more about the innovative work led by Dr. Chris Chen here: https://bdc.bu.edu/bdc-team/. What you’ll do: Independently conduct research on liver cell proliferation, expansion, and
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of induced pluripotent stem cell-based human disease models 2) Understanding the role of immunity during tumorigenesis as well as disease relapses in order to design novel inhibitors, CAR-T cell therapy and