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advances the mathematical foundations, algorithms, and real-world applications of epistemic uncertainty in machine learning, with a strong focus on imprecise probabilities, uncertainty representation and
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. Candidates having relevant research or working experience in LLM/VLM and AI decision-making algorithms for autonomous vehicles will be preferred. Good communications skills and the ability to work
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Responsibilities Development of new machine learning modeling approaches Development of new advanced control and optimization algorithms Optimization of carbon capture process operation Provide regular project
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Power Engineering • Relevant experience in power electronics, wide band gap semiconductor devices, multilevel inverters, soft-switching high-frequency power converters, drives, control algorithms
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and RISC-V architectures. Investigate various aspects of system design, including: Topology exploration, routing algorithms, protocol and flow control design Chiplet oriented and interposer design
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architectures. Investigate various aspects of system design, including: Topology exploration, routing algorithms, protocol and flow control design Chiplet oriented and interposer design strategies, SiP and
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Notebook; apply foundational knowledge of ML algorithms. Work closely with and provide guidance to interns and part-time student developers. Job Requirements: Preferably bachelor’s degree in Computer
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. The roles of this position include: Development of algorithms to improve memory/sample/time efficiency of LLM training. Development of a workable prototype system with capabilities such as conversational
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development team Interacting with Continental business areas Developing and integrating AI algorithms into the real development progress Preparing academic publications such as patent applications and research
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of projects. Job Description: The successful applicant will be responsible for Performing literature review and background study on collaborative AI Develop algorithms and system designs that can optimize