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optimization, AI, power electronics with good publication record· Good at coding in python with different DRL algorithms training, or good at digital platform development will be a preference Knowledge of
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writing scientific papers and communicating our research advances in conferences. Methods: programming a humanoid platform using ROS2 packages, solve SLAM, use imitation learning algorithms to learn pick
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properties. In this project, we will apply machine learning and optimization algorithms in order to achieve the design of such nanophotonic structures. As a postdoc you will be part of the Condensed Matter and
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apply machine learning and optimization algorithms in order to achieve the design of such nanophotonic structures. As a postdoc you will be part of the Condensed Matter and Materials Theory division, a
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, or equivalent, with excellent knowledge of digital communications and signal processing. High grades in the core courses are required. Skills in mathematical analysis, modeling, and network algorithms
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on Bayesian methods for real-time, risk-aware trajectory planning in autonomous driving. Develop, implement, and evaluate algorithms for scenario pruning, control action selection, and reachability analysis
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, machine learning or similar. Alternatively, you have gained essentially corresponding knowledge in another way. The applicant is expected to have good knowledge of computer science, mathematics, algorithms
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questions include automated modeling and model simplification/refinement supported by generative AI, system identification, and 3D reconstruction algorithms. Additionally, the research involves developing
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, resource efficient algorithms, and programming paradigms for enabling an application-tailored design of dependable communication and computation systems. Project description This PhD project is linked
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an integrated development of network architectures, resource efficient algorithms, and programming paradigms for enabling an application-tailored design of dependable communication and computation systems