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University of Illinois at Urbana Champaign | Springfield, Illinois | United States | about 1 month ago
to think algorithmically. Accurate and precise attention to detail. Excellent analytical, quantitative, and organizational skills. Appointment Information This is a 100% full-time Civil Service 5002
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testing of model-free algorithms for real-time optimization of turbine operating conditions (e.g., yaw set points). Other projects may be assigned by the supervisor depending on skills and technical needs
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for this position is $107,100-$232,100, based on the current salary scale: https://www.ucop.edu/academic-personnel-programs/_files/2025-26/policy-covered-october-2025-scales/t3.pdf "Off-scale salaries” and other
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simulations on the Aurora supercomputer, using AMReX (https://amrex-codes.github.io/amrex/ ) and the lattice Boltzmann method (LBM). The candidate will develop flow/geometry-aware refinement strategies that go
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of social media trends, algorithms, and audience behaviours. Comfortable working with multiple stakeholders in a complex environment. Strong organisation and time management skills. A team player who
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of distributed MIMO, and/or coordinated multi-AP operation (under study in the Wi-Fi 8 standardisation workgroup), using Hardware Description Language on FPGA, based on the open-source openwifi project (https
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graduate students, etc. In particular, the MLE hired for this position will work with Ayan Paul and Hyunju Kim at EAI and is expected to develop AI algorithms for drug synergies with a combination of public
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in the Ph.D. Program in Physics. Applicants must also apply to the Visiting Scholar position in the Center for Computational Quantum Physics (CCQ) posted on the Flatiron Institute’s website at: https
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, quantum compilation techniques, and noise-aware algorithms for Rydberg architectures. Apply quantum optimization to real-world problems such as logistics, scheduling, and portfolio allocation, comparing
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scholarship holder will contribute to several research activities, including: - Design and implementation of event-based data compression algorithms, including lossy and learning-based approaches. - Development