318 coding-"https:" "https:" "https:" "https:" "https:" "NanoSci" positions at Nanyang Technological University
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, writing code that is clean, modular, and maintainable. MLOps & Cloud Proficiency: Fluent in the essential MLOps toolkit, including Git, Docker, and CI/CD principles. Have experience building data and model
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empirical and quantitative skills. 3. Has good coding skills. 4. Has good communication skills. 5. Visualization skills an added advantage. We regret that only shortlisted candidates will be notified. Hiring
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Engineering best practices, writing code that is clean, modular, and maintainable. MLOps & Cloud Proficiency: Fluent in the essential MLOps toolkit, including Git, Docker, and CI/CD principles. Have experience
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of relevant research experiences or equivalent Prior experience in working with embedded systems is required. Prior experience with coding and evaluation of cryptography algorithms, specifically Post-Quantum
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on implementation/experimentation, maintain best practices for coding, safety evaluation, and data handling. Expectations: high research ownership, strong experimental rigor, proactive problem-solving, clear
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the University and with external collaborators. Support project coordination activities, including documentation of research workflows, version control of code and data, and supervision or mentoring of research
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optimization Collaborate with product, research, and business teams to translate complex requirements into scalable solutions Mentor and technically guide engineers, conduct code reviews, and set engineering
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. Familiarity with industrial products’ standards and certifications, grid connection codes of different countries, etc. Good written and oral communication skills Proficiency in power electronics circuits, field
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and co-curriculum. Hence, NTU launched a new curriculum structure in 2021 featuring a range of ICC Courses. Learn more about the ICC Courses here: https://www.ntu.edu.sg/education/inspire
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categorical methods for describing and reasoning about modern AI systems. Formulate and verify mathematical properties of AI systems using rigorous, algebraic and code-based methods. Apply the developed