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Theoretical Quantum Many-body Physics and Quantum Sensing at Indiana University Bloomington Fields: Quantum many-body theory, AMO–condensed matter interfaces, advanced numerical simulations, quantum sensing
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team as a PhD candidate to work on beyond the state-of-the-art model distillation and robustness methods, enabling efficient, reliable inference for challenging real-world problems in the semiconductor
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) computational simulations to understand both the electronic states of enzyme intermediates and the transitions between them. As a joint studentship, around half of the project will be based in Manchester and half
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of algorithms and models to realistically simulate forest ecosystem dynamics under varying conditions of land use change, forest and land management, climate variability, and other environmental stressors
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, graph neural networks, physics-informed ML) to approximate PF results Train models using simulation results generated from conventional power flow solvers Evaluate AI-based approximators in terms
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scaled-up, optically clear model of the new dialyser. You will apply advanced techniques, specifically Particle Image Velocimetry (PIV) to resolve complex fluid flow behaviour. This role offers a unique
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conducted using high-fidelity CFD model such as Large-Eddy Simulation (LES). The work will include simulation of shallow boundary layer flows such as atmospheric flows with differing thermal stability and of
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topics such as statistics, high performance programming, machine learning and using data to constrain cosmological models. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs
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role model in secure trustworthy AI by pioneering cyber resilience across the AI lifecycle. The research program focuses on four key themes: Trustworthy and Verifiable AI, Runtime Security Assurance
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: Develop data-driven numerical models (opinion models, norm dynamics, multi-agent systems). Network Science: Study social and temporal interaction networks using network physics tools. Simulation: Conduct