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candidate is self-motivated and hard-working with a PhD in Data Science, Computational Social Science, Computer Science, or Information Science, with no more than five years post receipt of the PhD
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 2 months ago
Studies (WOS) group at MIT Sloan. Ideal candidates will have recently completed a PhD—or be near completion—with a research agenda relevant to management. Degrees may be in psychology, sociology
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for conferences, grant proposals Data analysis and pipeline development Technology-based solutions for advancing population health To be eligible, candidates must: Have received a PhD in computer
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volunteers Performs other duties as needed Required Qualifications PhD degree in biomedical engineering, electrical engineering, computer science, biostatistics, or a related field Preferred Qualifications
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, the scholar will be responsible for building and maintaining AI-assisted meta-analyses. The scholar will also be responsible for improving generalizable knowledge about the trustworthiness in AI literature
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significant and sustained growth period and seeks to build on existing strengths while expanding its impact. Candidates with a strong background in any area of Mechanical Engineering are encouraged to apply. We
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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
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). Experience in neurotechnology development: hardware adaptation, electronics, device building, or related engineering skills. Background in neurodevelopmental research and/or in vivo recordings in juvenile
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Job Purpose To make a contribution to an ERC-funded project Dynamic network reconstruction of human perceptual and reward learning via multimodal data fusion, working with Prof. Marios Philiastides
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the direction of the Principal Investigator in building a first-of-its-kind Software as a Medical Device (SaMD) that predicts, detects, and manages SSIs by fusing RGB + thermal wound images