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data in near-term era quantum computers. Applicants with backgrounds in quantum information or particle physics are both encouraged to apply. Candidates with strong expertise in machine learning, quantum
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and at national/international conferences. ● Collaborate with an interdisciplinary team of biostatisticians, computer scientists, climate scientists and community and industry partners. ● Contribute
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The Computational Science and Engineering Laboratory at Harvard University invites applications for postdoctoral position at the interface of scientific Computing and Artificial Intelligence for applications
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Models Basic Qualifications: A Ph.D. or equivalent degree in Machine Learning, Computer Science, Electrical Engineering, Geophysics, Applied Mathematics, or a closely related field. Demonstrated strong
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statistics, computing, machine learning (ML), and genetics and genomics, with a focus on large-scale genetic, genomic, and phenotype data. The work will involve both methodological research and collaboration
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program, or employed by a non-profit organization, as an undergraduate, postbaccalaureate, graduate, or post-doctoral trainee. Individuals who have previously received a professional development award from
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possible. Basic Qualifications PhD in computer science, statistics, electrical engineering, applied mathematics, computational biology, or a related quantitative field required by the expected start date
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—are intended to foster the early career development of researchers who have transitioned or are transitioning from training environments in the physical/mathematical/computational sciences or engineering into