287 coding-"https:"-"Prof"-"FEMTO-ST" "https:" "https:" "https:" "https:" "https:" "P" positions at Nanyang Technological University
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data coding and analysis (SPSS, Nvivo) Excellent communication skills, including academic writing Personal attributes Independence and proactive stance toward work tasks Good interpersonal skills
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measurements, the candidate will assess the classroom environment and teacher-child interactions, administer standardized developmental tests, and contribute to behavioral coding and data analysis. The incumbent
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of statistics and machine learning models Proficiency in coding using Python Knowledge of biomechanics and computer vision is a plus Experience in the following skills is a plus: (1) biomechanics software (e.g
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development and debugging experience Solid understanding of fundamental machine learning and AI techniques Knowledge of computer graphics and interface design Fluent in coding with generative AI Creativity
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guidance. Develop documentation, training materials, and reusable code templates. Requirements Bachelor’s degree in Computer Engineering, Sciences or its equivalent. Hands-on experience with CUDA, OpenCL, C
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to code in Python Able to write academic papers Responsibilities: Liaison with school and MOE partners Organisation of meetings Coordinating with other team members Conduct literature reviews Assist in
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advanced proficiency. Working knowledge of widely used statistical tests. Functional proficiency in statistical coding using R, Python, or similar programming languages. Proficiency in written and spoken
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operational aspects Strong organisational and multitasking skills, with the ability to prioritise and manage multiple tasks and responsibilities Possess professional values that are in line with the Code
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the ability to prioritise and manage multiple tasks and responsibilities Possess professional values that are in line with the Code of Ethics of SAC Possess good interpersonal and communication skills
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Responsibilities: Conduct and coordinate extensive software coding on the latest research platforms, Gain familiarity with existing research on diffusion models, particularly in relation to conditioning and guidance