79 algorithm-development-"Multiple"-"Simons-Foundation" "Prof" Postdoctoral positions at Princeton University
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interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials
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their departments and can acquire a breadth of expertise by working with multiple faculty members. We value building a culturally diverse intellectual community; women and members of underrepresented groups
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scientists for research and development activities focused on data science and engineering. The scientist will collaborate with Princeton and GFDL researchers to enhance, analyze and deliver high-resolution
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revolutionize the understanding and advancement of human health by conducting interdisciplinary foundational research, developing and harnessing advanced computational approaches, and training the next generation
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project, the appointee will have opportunities to develop additional projects with members of Dr. Sinclair's lab and/or maintain their on-going work. The work location for this position is in-person
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-year appointments. In addition to the aforementioned project, the appointee will have opportunities to develop additional projects with members of Dr. Vélez's lab and/or maintain their ongoing work
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project. The ideal candidate will have experience in yeast strain development and engineering CRISPR-based control of gene expression. This position will allow for both professional and laboratory skill
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technologies. The Pritykin lab (http://pritykinlab.princeton.edu ) develops computational methods for design and analysis of high-throughput functional genomic assays and perturbations, with a focus on multi
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develop methods for the synthesis and analysis of systems producing renewable fuels and chemicals; and use these methods, in collaboration with other researchers at Princeton and other institutions
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of whole genomic data already available; and ii) investigating rates of evolution across the genome and their correlation with phenotypic traits across various subdivisions of the squamate body plan