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learning methodologies. The underlying data are complex and will require sophisticated data management and integration skills. A candidate should have proficiency with GIS software and Python, strong written
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of decarbonized water and energy systems; and 3) supporting the design and enforcement of water-energy-food policies. We seek a new team member who enjoys team-science and engineering and would thrive
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. Prevalent TCR clones will undergo reverse engineering to deduce the peptide bound, and this information used to generate MHC tetramers to study the induction of these clones during the anti-tumor response
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for teachers and school leaders to implement evidence-based decision making. This position will involve collaborative work with a team of researchers, engineers and partnership coordinators on building out
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decisions are made under pressure, and how technology can support (rather than hinder) patient care. The postdoctoral scholar will use modern data science tools and cloud computing to analyze high-dimensional
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scientific research on computational linguistics, machine learning, practical applications of human language technology, and interdisciplinary work in computational social science and cognitive science. The
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spatial genomics experiments is a plus but not necessary. Experience in carrying out independent and collaborative research. Proven experience with protocol development, software development, computational
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of infectious diseases research and provides a strong community of scientific colleagues and students. Required Qualifications: The ideal candidate will have a PhD in Epidemiology, Engineering, Data Science
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.) and proficiency in data analysis software (such as R, Mplus, SPSS). Extensive experience interpreting research data and summarizing findings via written reports and oral presentations. Strong record
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closely with a multidisciplinary team including physicists, radiation oncologists, biologists, and engineers. Key Responsibilities: Deliver and optimize ultra-high dose rate (FLASH) radiotherapy to small