19 development-"https:"-"https:"-"https:"-"https:"-"VUB" Postdoctoral positions at Harvard University
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Dana Foundation Professional Development Awards Eligibility: Applicants must be currently affiliated with an academic or non-profit institution in the United States and enrolled in a training
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FAS Office of Postdoctoral Affairs: Postdoctoral Awards for Professional Development (PAPD) Deadline Month: This program is currently on pause. Description: These awards are designed to support the
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institutional leaders to design, implement, strengthen, and broaden postdoctoral fellowship experiences for scientific advancement and professional and career development in the Harvard Longwood community
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projects, acquire and analyze experimental data, supervise and mentor undergraduate students, prepare and submit peer-reviewed journal articles, and present their work at professional conferences. They will
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motivated Postdoctoral Research Fellow to develop and apply innovative, data-driven models for seismology, with a focus on developing cutting-edge foundation models. This is an exceptional opportunity
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the intersection between quantum information and particle physics. The successful applicant will work in Professor Carlos Argüelles’ group on the development of new algorithms to encode and process particle physics
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of support for the career development activities for underrepresented postdoctoral fellows in a degree-granting institution (an institution includes its affiliated graduate and medical schools, hospitals and
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-time Postdoctoral Research Fellow to join the causal inference team supervised by Professor Francesca Dominici. The position will focus on developing and applying novel causal inference methods for large
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impact. Our team leverages data pipelines to quantify data centers’ electricity and water use, emissions, and air pollution exposure and health impacts. The overarching goal is to develop an interactive
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developing next-generation AI methods for healthy climate adaptation. The position will focus on building and evaluating foundation models for large-scale spatiotemporal health and environmental data. Our team