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the computational science community. We empower researchers to tackle some of the most complex global challenges through our unique blend of supercomputing resources and computational science expertise. The ALCF is
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complex sociotechnical systems Strategic learning and equilibrium-seeking algorithms in transportation networks Game-theoretic approaches to cybersecurity and security games Integration of human behavior
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areas: infrastructure systems modeling, emissions inventory development, air quality modeling (chemical transport models and/or reduced-complexity models), exposure assessment of airborne pollutants, and
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link various actors within the complex area of climate change. The successful candidate will be working in different case study in Europe under the frame of the EU Project NBS4Droughts. The primary goal
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Job Description Who are we? The Texas A&M Transportation Institute (TTI) is an agency of the State of Texas and member of The Texas A&M University System. For 70 years, TTI has addressed complex
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modeling tools to develop and optimize new processes and equipment designs using high-performance computing Analyze data, prepare manuscripts for submission to peer-reviewed publications, prepare technical
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in order to integrate existing competences and knowledge, and to link various actors within the complex area of climate change. The successful candidate will be working in different case study in
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systems (ITS). In particular, the successful candidate will conduct cutting-edge research in: Developing physics-informed neural networks (PINNs) for complex dynamical systems modeling and observer design
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Job Description Are you looking to grow your career in intelligent embedded systems and edge computing? Join the Embedded Systems Engineering (ESE) research section at DTU Compute , where your
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, Mechanical, Thermal Engineering or Computer Science. Experience Experience in conducting high quality academic research. Demonstrable ability to write material of a quality commensurate with publication in