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” focusing on the effect of a fluctuating environment on the collective dynamics of self-propelled agents, a numerical part on “reinforcement learning” focusing on optimizing communication between agents in a
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, with a focus on arboviral diseases (e.g., dengue or Oropouche viruses). Other projects include improving risk assessment, optimizing surveillance system design, and developing and evaluating mitigation
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of non-native species in forests, economic optimization of forest biosecurity, and the global impacts of invasions on global forest ecosystem processes. We encourage applications from candidates of all
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minimization, robust optimization, deep learning for systems, probabilistic data management, or decision-making in uncertain environments are a prerequisite. Successful candidates will also demonstrate a
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or equivalent Skills/Qualifications As a Postdoctoral Researcher: You will be responsible for establishing and optimizing assays to capture enhancer-promoter interactions (e.g., 4C, Hi-ChIP) and to analyze
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Required Knowledge, Skills, and Abilities Preferred Qualifications Experience with process design/synthesis/optimization and TEA. Experience with relevant tools (e.g., Aspen Plus, SuperPro Designer
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Required Knowledge, Skills, and Abilities Preferred Qualifications Experience with process design/synthesis/optimization and TEA. Experience with relevant tools (e.g., Aspen Plus, SuperPro Designer
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-relationships, materials optimization, materials under extreme conditions, and generative AI. Candidates must possess substantial experience in artificial intelligence and machine learning methods, specifically
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Department of Chemical and Biological Engineering at Princeton University. The position is in the broad area of renewable energy systems synthesis, analysis, and optimization. The goal of the project is to
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optimizations are still needed to adapt the translation of these mRNAs to the cell types of interest. As part of a collaboration with Chantal Pichon's team (University of Orleans), this project aims to use