2,261 computer-science-intern "https:" "https:" "https:" "https:" "UCL" "UCL" positions in Singapore
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academia, industry, and national laboratories Job Requirements: PhD in Materials Science, Chemistry, Physics, Computer Science, or a closely related discipline. Strong experience with Density Functional
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include: (1) Strategic positioning of the programme to build on its reputation and visibility in the international arena; (2) Managing and overseeing curricular content and manpower needs
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expertise in optimisation; Computer Science, with expertise in design and analysis of algorithms and high-performance (GPU) computing; Industrial and Systems Engineering, with AI in process mapping and Conops
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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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within OIE, leads initiatives such as the Duke-NUS Healthcare Innovation Programme (D-HIP), a unique programme that nurtures future clinician and healthcare innovators and develops solutions to unmet
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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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the planning, coordination, and execution of academic and clinical education initiatives. Liaise with internal departments and external organisations to coordinate programme collaborations, partnerships, and
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Organization: College of Design and Engineering Department : Electrical and Computer Engineering Employee Referral Eligible: Job requisition ID : 31376 Apply now
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processes with internal stakeholders. Maintain and update data-related SOPs and user guides. Stakeholder Coordination and Operations Support Act as a key coordination point with the University Advancement
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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