52 data-"https:"-"https:"-"https:" positions at SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
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Management or a related field (e.g., Data Analytics, Big Data, Entrepreneurship, Asset Management, AI), preferably with extensive management experience in the hospitality and tourism business, excellent
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modelling, CFD mesh generation in complex 3D geometries. Proficient in handling large data sets and the ability to analysis and interpret results. Experience in commercial CFD package such as ANSYS package
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. Ubuntu) Experience with version control systems (e.g., Git or CVS). Knowledge and some practical experience in areas such as Reinforcement Learning (RL), imitation learning, motion planning, computer
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, data collection, and analysis. Industry or research lab experience is required. Strong analytical and conceptual abilities. Ability to work in a team as well as independently. Able to work under pressure
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(Research Engineer) Bachelor/Master degree in Computer Science or a related field Proven ability to conduct independent research with a relevant publication record. Outstanding data analytics, mathematical
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. Supported Areas for START - Infocomm Technology Information Security: Mobile security, cyber-physical systems, IoT security, security analytics, operational cybersecurity, digital forensics, vulnerability
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and oversee a range of cybersecurity enablement programmes to facilitate the growth of information security skills among SIT undergraduate students and academic staff. Stay up-to-date with the latest
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offloading strategy via simulations and live demonstrations. Job Requirements A Ph.D degree in Computer Engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly analytical
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safety in labs. Job Requirements Education & Certifications: Bachelor’s or Master’s Degree in Software Engineering, Computer Science, or related fields from a recognized University. Major in Information
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operations. Process control: process modelling, control, and optimization, with applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in process