289 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" Fellowship positions in Singapore
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: Electrical and Computer Engineering Employee Referral Eligible: No Job requisition ID : 31794 Apply now
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quantum information theorists to integrate secure key rate calculations with simulations. Investigate and apply AI and machine learning techniques to improve and support secure-by-design development
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Computer Science, AI/ML, Computational Biology, Food Science with computational expertise, or a related field. Experience with natural language processing, machine learning frameworks (e.g., PyTorch
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nowcasting platform that delivers real-time, hyperlocal information on urban heat risks in tropical cities. Leveraging Doppler lidar–based microclimate studies and machine learning, the research emphasizes
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research program to develop next-generation sensor devices and systems for human-machine interactions. Qualifications PhD in Materials Sciences, Robotics, Mechanical Engineering, or related disciplines. More
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Corporate Laboratory is seeking to hire a Research Fellow. The selected candidate will innovate research in advanced materials. Key Responsibilities: Work on AI-driven techniques such as machine learning and
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, such as, geometric/topological/algebraic data analysis, geometric/topological deep learning, Math for AI, categorical deep learning, sheaf neural networks, PINN/KAN models, neural operators, etc, and
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expression systems Control of transcription, gene regulatory networks Synthetic biology, especially cell line engineering Immunotherapy, especially CAR-T/NK/M or dendritic cell therapies Diabetes, especially
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based on performance and funding availability. Review of applications will begin immediately and continue until the position is filled. Qualifications • PhD Degree in Electrical and Computer Engineering
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). Plan and draft cross-project analyses, synthesis sections, and learning summaries to disseminate CRCD research findings through publications and events (e.g., journal sections, pre-conference sessions