37 assistant-professor-computer-science-and-data Fellowship positions at Singapore Institute of Technology
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, Safety and Health Regulations. • Assist in project resource requirements and managing student projects. Job Requirements: • Have a PhD Degree in Computer Engineering/Computer Science/Electrical Engineering
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As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research stsaff will have the opportunity to be equipped with applied research skill sets
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As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets
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. Awards will be finalised by July 2026. Supported Areas for START Infocomm Technology Information Security: Mobile security, cyber-physical systems, IoT security, security analytics, operational
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be considered for Assistant Professorship. Eligibility and Selection Criteria Singapore citizen Doctoral candidates who have recently completed or are about to complete their studies in a discipline
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As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets
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be considered for Assistant Professorship. Eligibility and Selection Criteria Singapore citizen Doctoral candidates who have recently completed or are about to complete their studies in a discipline
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for undergraduate students. Interview and supervise student assistants in the project. Job Requirements (Research Fellow) PhD in Computer Science or a related field (Research Engineer) Bachelor/Master degree in
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Learning/Computer Vision. The experience in diffusion models is a plus. Have a PhD degree in computer science/engineering or related disciplines. Knowledge of autonomous vehicles or cyber security will be
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-on expertise in NGS workflows Have a degree in Biomedical Sciences, Biotechnology, Molecular Biology, Life Sciences, Biochemistry, or a related Bioscience field. Familiarity with NGS data analysis