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Field
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Scientific Machine Learning. The successful candidate will develop and deploy state-of-the-art SciML algorithms in high-performance computational physics codes. We accept applications from all candidates with
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NSF funded projects, advancing the knowledge about distributed systems, developing novel algorithms for distributed resource and workload management, simulating and emulating systems, as
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, calibration, and the development of analysis tools and software. Our key focus areas are the physics of jets, top quarks, and EWSB, including the development of novel machine-learning methods for high-energy
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. The primary project will involve developing system models for radio frequency spectrum allocation, coexistence techniques, and dynamic spectrum sharing approaches that integrate technical, economic, and
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: Proficiency in algorithm development for autonomous systems. Experience with ROS2, UAV simulation (e.g., AirSim), and real-time system integration. Strong programming skills in C++ and Python. Excellent
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Requisition Id 14997 Overview: We are seeking a postdoctoral fellow to help develop world-class capabilities related to manufacturing science and technology associated with the Oak Ridge National
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involve the development of novel lattice QCD algorithms and high-performance computing (HPC) codes, and/or exploring applications of artificial intelligence (AI) to lattice simulations. The starting date is
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motivated Post-Doctoral Associate to join our team with a strong background in robot control, machine learning, and differential geometry to work on the development of advanced algorithms to enhance
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the developmental rules underlying phenotypic variation. The successful postdoctoral fellow will develop and implement an empirical framework that utilizes data-driven algorithms to learn relationships between past
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design, development, and validation of material, control systems, and algorithms for next-generation soft haptic actuators and experiences. Note that the research involves significant interactions with