1,457 machine-learning "https:" "https:" "https:" "https:" "UCL" "UCL" positions in Singapore
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frameworks for advanced property prediction and analysis of inorganic disordered materials. Carry out machine-learning based first-principle calculations aimed at advancing the understanding defect-based
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related discipline. You must be a current machine learning, theory and atomistic simulations for material design. You must be an excellent communicator in English, both verbally and written. You must be
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insights from cutting-edge clinical and translational research. More information on the Department’s research portfolio may be obtained from https://medicine.nus.edu.sg/obgyn/. The Core Support Faculty will
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deployment enabling validation and demonstration of real-world applications. We are looking for a software engineer to develop and maintain scalable software applications with a focus on AI, machine learning
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delegated by PI Job Requirements Master qualification degree in Electronic Engineering or Computer Science Familiarity with pinching antennas and machine learning Good written and oral communication skills
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modalities of PET-CT and PET-MRI. For more details on what we do, do visit https://medicine.nus.edu.sg/circ/. Appointments will be made on a two-years contract basis with the possibility of extension
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Qualifications Education: - Doctoral degree in Computer Science, Biomedical Informatics, Data Science, Artificial Intelligence, Machine Learning, Educational Technology, or closely related field - Postdoctoral
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/Senior Lecturer at the National University of Singapore (NUS) Are you passionate about shaping the future of data literacy? Do you have a strong background in AI and Machine Learning, with a commitment to
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at NTU. Key Responsibilities: The successful applicant will be responsible for Obtaining rigorous mathematical results geometric optimization and applications to data science and machine learning Designing
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and acquire spectral data Perform Raman spectral data analysis using machine learning algorithms Work with DiSTAP plant biology collaborators, training researchers in spectrosocpy Work with local