155 condition-monitoring-machine-learning 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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., or equivalent is required. Applicants should have training and a significant track record in one of the following areas: -computational biology-computer science-electrical or computer engineering-genomics
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biology-experimental and/or theoretical biophysics-experimental and/or computational genomics-computer science, statistics, and/or machine learning with applications relevant to genomics-bioinformatics
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for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic
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UHS practices and services. UHS leverages clinical encounters and prevention efforts into meaningful opportunities for our members to learn about and adopt healthy living practices. UHS also supports a
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for our members to learn about and adopt healthy living practices. UHS also supports a public health approach that prevents or responds rapidly to illness outbreaks and injury, and advances, preserves
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. Postdoctoral Research Associates will devote their residency to writing about race in national or global contexts and, with the approval of the Office of the Dean of the Faculty, will teach one semester-long
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, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law. Expected Salary Range: $145,000 The University considers factors
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science, electrical and computer engineering, sociology, public policy, information science, communication, economics, political science, psychology, philosophy, and related technology disciplines. Selected candidates
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qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status