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interaction and analytics using AI. Key Responsibilities: Development of artificial intelligence (AI) technologies to perform human-robot interaction and analytics System integration of the developed algorithms
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and planning algorithm for high-speed autonomous vehicle. The work will involve algorithm development, simulation, test rig set-up, and experimental validation. Requirements: The candidate must at least
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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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frameworks (MOFs), and related materials using hybrid classical-quantum algorithms. A key component of the role involves using first-principles methods that capture strong electronic correlations, such as DFT
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algorithmic foundations of quantum adversarial machine learning, an emerging field at the intersection of quantum computing and machine learning. It investigates how the unique capabilities of quantum computing
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to remove PFAS. To accomplish these goals, the candidate will participate in the development of AI/ML algorithms for the prediction of chemical properties, infrared and mass spectra, and ionization cross
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cooperative, competitive, and mixed settings. Collaborative decision-making frameworks and decentralized learning algorithms. Adaptive, meta-learning, and context-aware strategies to enhance policy
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the following tasks: Development of new large language models for process modeling Development of new decision-making algorithms Provide regular project updates to principal investigator and funding agency Report
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for this role. This role will involve developing and applying analysis plans using a variety of advanced methods with the support of project supervisors. The postholder will have completed a PhD in a relevant
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Requirements: MSc (Research Associate) or PhD (Research Fellow) in Mathematics or Computer Science or closely related fields. Ability to design and implement advanced algorithms and data structures. Independent