186 evolution-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"U.S"-"U.S" Fellowship positions in United States
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. Modeling dynamical systems Designing and extending algorithms grounded in probabilistic machine learning Applying statistical techniques to assess robustness and generalization. Development of methods
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sciences. The research interests of the candidate can be one or more of the following topics. Projects that address change across time or across nations in different stages of development are encouraged
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. They will also have the opportunity to work on other problems related to global atmospheric chemistry, air quality, and model development. Basic Qualifications Ph.D. in atmospheric science and substantial
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pipelines. Fellows will gain hands-on exposure to translational science, drug discovery, and technology development, with opportunities to contribute to intellectual property, partnerships, and new venture
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School. KHRI and the neuroscience community at the U-M provide a highly supportive and diverse research environment and excellent career development opportunities for postdoctoral fellows. We are committed
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for a Postdoctoral Fellow position. The lab is working to explore the evolution of mammalian lifespan with the goal of better understanding the underpinnings of human aging. There is a strong emphasis on
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evolutionary life history theory, growth and development, endocrinology, nutrition, reproductive ecology or aging. Additional Qualifications Special Instructions Candidates should upload the following materials
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conferences. Contribute to proposal development and future research directions aligned with PRISM objectives. We are looking for: Ph.D. in Mineral Engineering, Chemical Engineering, Materials Engineering, or
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. The incumbent will prepare pension claims and appeal letters on behalf of PAC clients. In addition, the incumbent will assist the PAC Director and PAC Development and Outreach Director with raising money
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. This project involves the development and application of interpretable machine learning methods to uncover allosteric regulation of disordered regions in the dynamics of G-protein coupled receptors to enable