124 parallel-and-distributed-computing-phd-"Multiple" Fellowship positions at Harvard University
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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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(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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. 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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and professional development funding will be available. The aim of this program is to expand the pool of talented academic leaders equipped to conduct research that advances health equity using
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of this program is to expand the pool of talented academic leaders equipped to conduct research that advances health equity using the frames of social medicine. Fellows will be mentored to pursue the next phase of
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Quick Links: Program Description | Application | Funding | Eligibility | Terms of the Award | Confidentiality Agreements | Reporting | Publications | Forms for Awardees | Application
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Qualifications The Fellowship is meant for recent postdoctoral scholars who have completed their PhD studies in the last five years. For this year’s application cycle, applicants must have obtained their PhD
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Degeneration Research grant recipient, Yong-Su Kwon, PhD Our Funding Philosophy It is our firm belief that having the courage to invest in innovative ideas will lead to revolutionary therapies. BrightFocus
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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
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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