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Information Technology Are you interested in working with machine learning and simulation-based inference for searches for dark matter (or other “invisible” new physics signals) at the Large Hadron
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neural networks, and physics-informed machine learning in power systems Set up benchmark grids and generate or process suitable simulation data for power-flow, voltage-prediction, or state-estimation
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Australian National University | Canberra, Australian Capital Territory | Australia | about 14 hours ago
, even when they might appear conflicting. This project aims to forge an advanced framework uniting data science, machine learning, simulation, multi-objective optimization, and uncertainty-based
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Experience with machine learning applications in biology or genomics. Knowledge of population genetics theory and simulation methods. Experience developing or contributing to open-source software. The
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traffic-simulation platforms such as dSPACE, CARLA, SUMO, or comparable tools. Experience applying machine learning, computer vision, time-series analysis, generative AI, or sensor fusion to vehicle
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security, counterterrorism, cybersecurity. We provide technical leadership for the nation in scientific simulation, high-performance computing, scientific machine learning and extreme-scale data
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reactor. The work combines physics-based thermal design and process-level system simulation with high-fidelity computational fluid dynamics and fast reduced-order and machine-learning models, so that the
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Two postdoc positions in Thermofluid Design and Digital Modeling of Cooling Systems for Electroch...
process-level system simulation with high-fidelity computational fluid dynamics and fast reduced-order and machine-learning models, so that the final design is both experimentally realizable and
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, design principles and prototype tools that can be integrated into the ACT's simulation, analysis and optimisation workflows, fostering the adoption of mathematically grounded machine learning methods in
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simulation cases in tools like PeleLMeX for studying combustion in various burner geometries. Learning, maintaining, and enhancing the Kynema suite of incompressible solvers, including contributing new