103 computer-programmer-"https:"-"Prof" "https:" "https:" "https:" "https:" "https:" "UNIV" "Univ" Fellowship positions at National University of Singapore
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research, education, and services in data science, AI, and biomedical computation, building on existing institutional initiatives such as DAISI. We are seeking a highly motivated and talented Research Fellow
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imaging) and development of novel imaging techniques (nuclear and molecular imaging, computational imaging, etc). With the formation of the National University Health System (NUHS), both clinical and
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(or an equivalent degree) in Civil Engineering, Built Environment, Material Science or related fields. • Experience in research for structural optimization is desirable. • Strong computational analysis skills
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agencies. Qualifications • PhD in Robotics, Mechanical Engineering, Mechatronics, Computer Vision, or a closely related field. • Strong expertise in robot design and at least one of
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deliverables such as reports/journal articles, workshops and webinars. Qualifications Applicants should have at least or close to obtaining a PhD in the Social Sciences/Humanities, Computing or other relevant
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. This position focuses on the development and application of large language models (LLMs) for advancing food informatics, food bioactives research, and sustainable food innovation. The selected fellow
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Computer Engineering. More information on the laboratory is available at www.neuroimaginglab.org . The MNNDL group at NUS is a multidisciplinary team studying the human neural bases of cognitive functions
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Communicating with stakeholders to understand business challenges and potential solutions Qualifications Doctorate degree in a quantitative discipline (eg. data science, computer science, computational biology
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preparedness for effective disease outbreak management programme. Qualifications · PhD in Medical/Clinical Laboratory Science, Biomedical Sciences, Virology or equivalent degree. · Minimum 3 years’ postdoctoral
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experience with management and strategy research, economic modelling and statistical analyses are essential. Familiarity with data mining, machine learning and computation techniques, especially in the context