824 systems-science-"https:"-"https:"-"https:"-"https:" positions at Nanyang Technological University
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NTU is a world-class research-intensive university located in Singapore, consistently ranked among the top universities in Asia and the world. We are home to over 33,000 students and 10,000 staff
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Singapore’s AI-for-Science ecosystem. Key Responsibilities: The candidate is expected to conduct the following research works Develop and implement the "AI+Physics" discrepancy modeling framework to predict
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Robotic Process Automation (RPA) roadmap for SASD. A strong Digital Innovation and Transformation (DIT) team is crucial to drive the implementation of this roadmap, which will put in place a robust student
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Institute For Digital Molecular Analytics & Science (IDMxS) is a unique interdisciplinary Research Centre of Excellence (RCE), funded by National Research Foundation, Ministry of Education
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Executive, Automation Developer NTU Shared Services NTU Shared Services (NSS) is a centralized unit within Nanyang Technological University (NTU) that provides a wide range of administrative
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and accurate dissemination of information. Support faculty and adjunct lecturers in course delivery, including classroom logistics, educational technology tools, and Learning Management System (LMS
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cell biology, or related fields Prior research experience in a relevant field is advantageous Ability to work independently and collaboratively as part of a team RESEARCH FELLOW (BIOCHEMISTRY) Key
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Experience in the use of programming languages and interest in the implementation of algorithms relevant to the project The College of Science seeks a diverse and inclusive workforce and is committed
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safety and performance standards. Advise on integrating technological advancements, such as air traffic control systems (e.g., LORADS 3), to enhance operational capabilities and minimize delays
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screening, genome engineering, single cell cloning, to develop and optimise engineered cell systems Perform bioprocessing, cell-based assays, FACS, multi-omics and analytical workflows to assess genetic