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effectiveness of therapeutic agents and utility of biofluid biomarkers in pre/post-blast animal models, human volunteers and victims of blast exposure. It is fully anticipated that the multi-faceted experiences
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of agent-based and/or continuum modelling, analysis and simulation. You will have experience of programming in Python and C++, or demonstrated ability to rapidly acquire fluent knowledge of new programming
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related field in hand by the time of the appointment. Strong background in distributed control, optimization, or multi-agent systems. Proven track record of high-quality publications. Proficiency in
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standards regarding use of isotopes, chemicals, infectious agents, animals, human subjects, and the like. Open and timely discussion with the mentor regarding all facets of the Postdoctoral Appointee's
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writing C++ and PyTorch. Training and debugging RL agents. Imitation Learning algorithms for robotics or autonomous vehicles. Prior work combining RL with human data or feedback. A track record of code
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Campus Address Tucson, AZ USA Position Highlights The selected candidate will conduct research associated with the DoD-funded project "Nonlinear Oscillator Synchronization and Multi-Agent Consensus
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from geomatics, spatial analysis, multi-agent modeling and simulation, and laboratory work (soil and surface formation studies; host of the Solsup platform of the EMerode service unit). General
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oxides, specifically exploring the substitution of carbon with hydrogen as a reducing agent in iron and steelmaking. Both experimental and computational investigations of hydrogen reduction phenomena in
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. There will be three research fellows appointed in different stages of the project. For this post, the successful candidate will primarily focus on developing LLM agents to support effective theory of mind
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of simulation tools (e.g., Multiphysics finite element analysis, Matlab, Labview etc.) cleanroom experience, and characterization of electronic devices are required. Further, knowledge of system level integration