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Science, Computer Science, Applied Mathematics, Engineering and Physics. Additional Qualifications Expertise (or desire to work) in reduced order modeling, Causal inference and High Performance Computing
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statistical analyses on large databases Designing and running experiments Structural modelling and related econometrics Proving theoretical results Basic Qualifications Bachelor’s degree by start date (required
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of the primary objectives of the ITC is to integrate conceptual theory with computational modeling. We are, therefore, interested in candidates working in any field related to theoretical and/or numerical
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expertise in at least one (or more) of the following areas: Computer Architecture/Systems: Design, modeling, simulation, and/or physical design of heterogeneous system/processor architectures; Silicon
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research associates to develop and apply theoretical and computational approaches to study complex cell biological systems. The emphasis will be on combining statistical inferences and biophysical modeling
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of advanced technologies. This includes developing cutting-edge AI/ML models and datasets; learning how to take advantage of unparalleled computing resources in the academic environment by optimizing AI/ML
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of intelligence, including mathematical and computational models of intelligence, cognitive theories of intelligence, and the neurobiological basis of intelligence. Research and development of new AI or ML
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of Engineering and Applied Sciences. The fellow will design and run human experiments, perform data analysis, and create computational models of learning and memory. A PhD is required. An ideal candidate will be
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recruiting of fellows and partners across various fellowship models and sectors (PK-12; Higher Education). This includes: - Developing and managing a project plan for fellow recruitment (long term and short
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theoretical and computational approaches to study complex cell biological systems. The emphasis will be on combining statistical inferences and biophysical modeling to analyze single cell cross-sectional data