813 computer-science-intern-"https:"-"https:"-"https:"-"https:"-"BioData"-"BioData" positions at Nanyang Technological University
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internal and external engagements to promote the value and impact of our training programmes. Drive customer satisfaction and retention through proactive communication and after-programme engagement
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and PhD students on computational mathematics and AI methodologies. Job Requirements: A PhD degree in Applied Mathematics, Computer Science, Engineering, or a related quantitative field. Deep expertise
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of visual communications publishing platforms including print, event, physical/environmental, and digital properties such as School’s website and social media platforms. Work with other internal stakeholders
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to maintain excellence in research in mathematics and computer science. Skilled research staff working at this frontier research field is an essential human resource towards generating new knowledge and
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requirements include: Candidate should minimally hold a master’s degree in maritime transport, marine technology, computer science, or a related field. Excellent programming skills, such as Python, Matlab, C
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of Humanities, Arts and Social Sciences (COHASS). This position is intended for eminent overseas academics-such as international prize recipients or distinguished scholars-whose presence will enhance the academic
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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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strategic research development, programme-level integration, synthesis, dissemination, and collaboration activities. This role offers an exciting opportunity to contribute to centre-wide research outputs
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Nanyang Technological University Singapore (NTU Singapore) is a young and research-intensive institution, with more than 30,000 students in engineering, business, science, humanities, arts, social
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superlattices (twistronics). The role will focus on developing and applying theoretical models and computational quantum chemistry and machine learning methods to uncover novel properties and phenomena in low