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, design, implement, and validate an optimization system for scheduling group classes within the Koachy platform. The specific goals include: Develop attendance prediction models for different types
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. This role will contribute the development of novel machine learning algorithms for wireless sensing and communication and the proof of concepts for next-generation wireless communication, collaborating with
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Postdoctoral Research Fellow in Multimodal Foundation Models and Biomedical AI – AI/CS-Oriented Role
Develop and implement novel AI models and learning algorithms for multimodal and generative modeling. Collaborate with neuroscientists, clinicians, and AI researchers on interdisciplinary problems involving
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Massachusetts Institute of Technology (MIT) in Cambridge, Massachusetts. Your key responsibilities will be to: design and implement mathematical algorithms, and facilitate their integration into Magma engage with
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, Massachusetts. Your key responsibilities will be to: design and implement mathematical algorithms, and facilitate their integration into Magma engage with users, researchers, and developers, both internally
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-forming converters and control algorithms for next-generation renewable and energy storage systems. The role will focus on control design, simulation, and experimental validation to support system stability
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-edge research in machine learning and automated reasoning for safe algorithmic systems. The Research Fellow will be responsible for developing advanced theory and machine learning algorithms
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Matter Physics o Physical Chemistry and Theoretical Chemistry o Combinatorics, Algorithm, Extremal Graph Theory, Computing Theory o Programming Language, AI Theory or Machine Learning o Classical and
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and optimisation algorithms, focusing on their practical application in the context of the RaceEngineerAI project. Tasks include: - Developing models capable of simulating the behaviour of racing
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work with hands-on offloading algorithm design and development for IoT networks. The core responsibility is to build and validate edge-assisted offloading strategies, complete with software APIs, through