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systems for accelerating computational catalysis and experimental design. The successful candidate will contribute to building AI-native frameworks that combine first-principles modeling, machine-learning
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Job Description Applications are invited for a National Science Foundation funded (LEAP HI Program #2051685), Postdoctoral Associate position with the System Performance Laboratory (SPL
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minimum of one year eligibility remaining. • Strong background in computational modeling, AI-assisted modeling, microbial testing, or paper chemistry and structural evaluation. • Experience with fiber-based
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and collaborative researcher with expertise in engineering, materials science, or related computational fields to contribute to our research program focused on transport packaging optimization and
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, and archiving technologies. • Experience with task automation and wholistic management of enterprise workstation environments. • Understanding of the OSI model for computer network environments
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quantitative research experience in ecosystem modeling, environmental forecasting, and/or computational ecology, demonstrated by publications and/or software development -Significant experience working in the R
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: development of computational methods; maintenance of current models and data sets; and identifying and testing alternative data sources. Maintain detailed design specifications and written documentation
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(USN&WR). The successful candidate will have a research focus in computational geomechanics, emphasizing numerical investigation of soil behavior under coupled mechanical, hydraulic, and thermal
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to support research efforts focused on animal models of chronic pain using a variety of techniques. The majority of time will be devoted to research efforts, with a smaller proportion of time devoted to lab
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areas: formal verification, proof assistants and verification tools, binary/program analysis, or compilers. - Strong expertise with formal methods tools (e.g., theorem provers, SMT solvers, model checkers