173 programming-"https:"-"Inserm"-"FEMTO-ST" "https:" "https:" "https:" "https:" "https:" "UCL" Fellowship positions at Nanyang Technological University
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The NTU AI-for-X Postdoctoral Fellowship (AI4X-PDF), jointly supported by Nanyang Technological University (NTU) and Singapore’s National Research Foundation (NRF), is a prestigious programme
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Requirements: A Ph.D. degree in a related discipline (transportation engineering, computer engineering/science, or related disciplines) by December 2025. Expertise in AI, deep learning, and programming (e.g
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), information science, or related fields. Prior experience and proficiency in working with large language models including programming, evaluating, and benchmarking, evaluating. Demonstrated skills in quantitative
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Conceptualise studies and develop research designs Plan, execute, and manage research projects end-to-end Analyse data and synthesize findings Disseminate research through publications, presentations, and
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, documentation, and presentations) - essential for data analysis and communication with stakeholders Proficiency in hard skills, such as programming (Python, C++), machine learning frameworks (PyTorch, TensorFlow
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Proficiency in scientific programming and simulation tools (e.g., Python, MATLAB) Proven ability to conduct independent research, publish high-quality work, and collaborate effectively Strong written and oral
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necessary lead relevant meetings. To undertake any other duties relevant to the programme of research. Job Requirements: PhD degree in Computer Engineering, Computer Science, Electronics Engineering or
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Responsibilities: Conduct programming and software development for graph data management. Design and implement machine learning models for optimizing graph data management. Conduct experiments and evaluations
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simulation for physical systems. Strong foundation in mathematical modeling, simulation and quantum mechanics. High proficiency in scientific programming (Python, C++, MATLAB, or similar), with experience in
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. Experience handling complex, multi-modal datasets (e.g., biological, imaging, environmental, or data). Proficiency in programming languages such as Python and familiarity with machine learning frameworks (e.g