161 parallel-and-distributed-computing-phd-"Multiple" Fellowship positions at Harvard University
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contribute to technical deliverables and help to plan for technology translation. Basic Qualifications PhD in engineering, biomechanics, or a related field. Additional Qualifications Interest in
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Expected Start Date: July – Sep 2025 Basic Qualifications A PhD in Bioengineering, Biomedical Engineering, Electrical Engineering, Mechanical Engineering, and/or Neuroscience Extensive experience with
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, including research areas covered by the Euratom Research and Training Programme. Researchers interested in PFs should have a PhD degree at the time of the deadline for applications. Applicants who have
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to Contact With Questions Focus Areas Explore All Focus Areas Arctic and Antarctic Astronomy and Space Biology Chemistry Computing Creating a STEM Workforce Earth and Environment Education and Training
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their PhD in economics, business, psychology, public policy, political science, environmental science, statistics, or related fields, and whose research interests include private sector initiatives aimed
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scholars who have recently completed their PhD in economics, business, psychology, public policy, political science, environmental science, statistics, or related fields, and whose research interests include
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scholars who have recently completed their PhD in economics, business, psychology, public policy, political science, environmental science, statistics, or related fields, and whose research interests include
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and statistical genetics. Potential research projects include (but are not limited to) developing statistical methods and theory for large-scale multiple testing, variable selection, spectral clustering
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(yes, that means some museum and fieldwork!). Comparative analysis using advanced computational tools and wet lab techniques. Hands-on dissections of invertebrates for anatomical and physiological
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especially encourage candidates with proven experience in applying computational and experimental methods to social scientific questions – including aptitude in working with large-scale datasets and text