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, Algorithm, Extremal Graph Theory, Computing Theory o Programming Language, AI Theory or Machine Learning o Classical and Quantum Algorithm for Computational Quantum Many-body Theory o Theory and Computation
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for autonomous driving. This project aims to advance the state of the art in visual perception algorithms and real-time systems for autonomous racing, pushing the boundaries of performance, speed, and precision
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literature review, algorithm design, experiment design, model training, evaluation, and benchmarking. Work with and supervise undergraduate or graduate student assistants, guiding them in data collection
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. Experimentation & Implementation - Develop and implement the related algorithms, models, and techniques. - Perform rigorous benchmarking and evaluation of the developed models. - Optimize algorithms for efficiency
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for autonomous driving. This project aims to advance the state of the art in visual perception algorithms and real-time systems for autonomous racing, pushing the boundaries of performance, speed, and precision
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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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research and travel expenses. Relevant areas of expertise include: algorithms and complexity, natural language processing, and knowledge of the algorithmic fairness literature. The postdoc will be mentored
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Processing and Machine Learning to develop signal processing and machine learning algorithms and methods for communication networks. Key Responsibilities: Develop signal processing and machine learning
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of the project is to develop new theory and algorithms for massive datasets, with a particular focus on online algorithms related to numerical linear algebra. Key Responsibilities: The main duty of this position
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model checkers; proofs of safety and/or security properties; programming languages and/or type systems; concurrent and/or distributed algorithms; and related topics. The successful applicant will work in