219 parallel-and-distributed-computing-phd Fellowship positions at Harvard University
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fitness and tumor initiation. We welcome applications from recent PhD graduates who have published their thesis research and who are interested in this research area, particularly those who may have prior
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of innovation and digital transformation. Candidate Profiles: We seek candidates with strong quantitative and computational research skills in one of the following areas: Economics: PhD in Economics or Strategy
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Life Sciences Research Foundation: Postdoctoral Fellowships Eligibility: Non-U.S. citizens must work in a U.S. laboratory. Individuals who have held a PhD or MD degree for more than 5 years
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include online exhibitions, development of syllabi and lesson plans, a museum and garden tour focused on plants, etc. The Fellow will also teach in the Plant Humanities Summer Program . The Fellow will
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· Communicate project progress and coordinate with research team Duration: · 3 ½ months Preferred start date as soon as possible but flexible. Basic Qualifications: · PhD or equivalent in engineering, building
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for candidates interested in developmental, stem cell, neuro, computational biology, genetics or genomics. Basic Qualifications The candidate should have a PhD or plan to defend their PhD in the coming year
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. Some areas of particular interest include: genetics, evolutionary biology, neurobiology, developmental biology, and stem cell biology. Our lab uses both experimental and computational approaches
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Duration: · 3 ½ months Preferred start date as soon as possible but flexible. Basic Qualifications · PhD or equivalent in engineering, building science or related field Additional Qualifications · Strong
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L'Oréal USA for Women in Science Fellowship Eligibility: U.S. citizenship or permanent residency required. Candidates must have completed their PhD and have started in their postdoctoral research
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have a PhD in physics, biology, or a related field by the time of appointment. The ideal candidate will also have demonstrated experience in machine learning and biological data analysis and a strong