70 algorithm-development-"Prof"-"Prof" Postdoctoral positions at Princeton University
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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 on campus at Princeton University
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
to develop hybrid models for sea ice that combine coupled climate models and machine learning. Our previous work has demonstrated that neural networks can skillfully predict sea ice data assimilation
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development. Former postdoctoral researchers with SGS have pursued careers in academia, nongovernmental and international organizations, and in government (including in the executive branch and congress) as
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position to work on a new collaborative project in a team with expertise in plasma and plasma-surface interactions, surface science, and quantum metrology. The overall goal of the project is to develop
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Brazil, to fill Postdoctoral Research Associate or more senior research positions. Although the call is open, scholars working on policy and public health, or on economic development in the region
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develop and apply computational approaches for mass spectrometry data, with artificial intelligence/machine learning (AI/ML) being a major focus. They will have an opportunity to lead and contribute to a
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, collaborative, and vibrant research environment. Princeton University is in an idyllic college town halfway between New York City and Philadelphia, with convenient train access to both cities. This opportunity is
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to apply and further develop their technical skills in a dynamic research environment. The successful candidate will have the opportunity to work closely with our engineers and other research staff. Projects
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Branch is dedicated to accelerating the study of metabolic phenomena associated with cancer to develop new paradigms for cancer prevention and treatment. Its main research areas include: - Metabolic
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Fellows Program. The Program recognizes and supports outstanding early-career scientists who can make important research contributions in the areas of ecology, evolution, and/or behavior, while also