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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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                . 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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                algorithms, including machine unlearning techniques, to enhance model robustness and reliability. Design and execute rigorous AI testing frameworks to assess and mitigate risks in AI systems. Collaborate with 
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                : The successful applicant will be responsible for: Obtaining rigorous mathematical results at the interface of optimization, geometry, and data science Designing, implementing, and testing algorithms Engaging in 
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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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                goals, formulating contact-rich robot manipulation as a planning problem using haptic-based algorithms Coordinate with the extended research team in hands-on experiments for contact-rich manipulation 
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                . Develop and enhance advanced optimization algorithms for the Energy Management System (EMS), addressing energy dispatch, storage control, load scheduling, and strategies for market participation. Architect 
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                Responsibilities: Undertake research on algorithms and data systems for next-generation data preparation and data cleaning for data analytics. Produce research papers, reports, and presentations as required by 
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                algorithms, including machine unlearning techniques, to enhance model robustness and reliability. Design and execute rigorous AI testing frameworks to assess and mitigate risks in AI systems. Collaborate with