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Postdoctoral position. This position is available to individuals with research interests in applications of machine learning and artificial intelligence to wearable sensor data for nutrition research
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Computer Science, Mathematics, Physics, Applied Economics, or a related quantitative field. Skills and Knowledge: Knowledge of scientific computing, data assimilation, and machine learning frameworks. Proficiency in
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with a PhD in computer science or bioinformatics are encouraged to apply. We create statistical, machine learning, and deep learning approaches for the processing of this data, with a major focus on
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health records (EHR), waveforms from bedside monitors, radiology images and wearable sensors. This position offers a unique opportunity to work closely with clinicians on applications of machine learning
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position, funded by ALRI, offers an initial one-year appointment, with renewal contingent upon availability of funding. Conducts cutting-edge research in artificial intelligence, machine learning, and data
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antigens, T cell receptor (TCR) and antigen interactions and their crucial role in anti-cancer immune responses. You'll leverage your strong background in computational biology, machine learning, and
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work that underpins the scientific research of the collaboration. Research Title: Coupling Computation and Machine Learning to evaluate PFAS Chemicals The work will entail: The position is for a
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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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School of Engineering and Applied Sciences at Harvard University invites applications for a postdoctoral position in robot learning, beginning in September 2025, or soon thereafter. The position is for one
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collaborative, impact-focused problem solver who wants to be part of a dynamic team. Information about the Shih Lab: Learn more about the innovative work led by Dr. William Shih here: https