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for the direct spatio-temporal measurement of the turbulent dissipation rate at a solid wall. New post-processing algorithms are also developed for Particle Image Velocimetry to measure extremely dense 3D time
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/functional inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and
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transcriptomic technologies and biological data interpretation is a plus. Familiarity with optimizing cell segmentation algorithms for enhanced accuracy and efficiency, as well as experience with tools/packages
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of privacy-preserving artificial intelligence for the benefit of humanity. What You Will Do: Research (Federated Continual Learning): You will develop novel and privacy-preserving algorithms that allow
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Algorithms. The candidate is expected to conduct research in computer science focusing on the combinatorial aspects of quantum experiments and quantum algorithms for computational geometry problems. Prior
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interactions, nuclear structure and reactions, electroweak structure, and lepton-nucleus scattering. The candidate will contribute to advancing statistical and computational algorithms to extend the capabilities
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data for model calibration and validation. Apply sensitivity analysis and optimization algorithms to refine model parameters and improve predictive accuracy. Contribute to code development, documentation
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interaction and/or surface flux computation, including familiarity with bulk flux algorithms and observational QA/QC procedures. Experience with processing, analyzing, and interpreting multi sensor
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, through digital participation platforms, algorithms for identifying safe and sustainable routes, multimodal mobility hubs, as well as interactive simulation and visualisation tools for designing urban
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algorithms for battery management systems (BMS) in electric mobility and micro mobility applications. The primary focus will be on creating and optimizing state-of-charge (SOC) and state-of-health (SOH