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Snr Software Engineer, AI Centre for Educational Technologies - School of Computing (1year contract)
The AI Centre for Educational Technologies (AICET) is a research centre that is focused on developing technologies to improve learning. AICET collaborates with the Ministry of Education, Singapore and
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, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an ‘exciting place to learn and grow. We welcome you to join our community
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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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machines safely. (Capacity ranges from 10kN to 1000 kN). Providing good guidance on how to operate the hydraulic actuators safely (Capacity ranges from 1000 kN to 20000 kN). 3. Procurement and inventory
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for active learning. The role will work at the intersection machine learning, high-throughput computation, and inorganic crystalline materials discovery, focusing on accelerating the design and
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research team as a Research Engineer. The successful candidate will support ongoing research initiatives by applying advanced machine learning, NLP, and large language models (LLMs) to develop next
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, especially Python, Java, C. Knowledge in software engineering, data structures & algorithms, computer organization, artificial intelligence & machine learning is a plus. More Information Location: Kent Ridge
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of spatial models especially land-use regression model or machine learning EOS seeks a diverse and inclusive workforce and is committed to equality of opportunity. We welcome applications from all and recruit
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discipline, with a focus on Cyber Security, Machine Learning and/or Data Mining Strong publication records in reputable journals/conferences Excellent programming skills in e.g., Python, Matlab, C++, etc Good
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to disaster events, and mapping ocean colours and ocean topography for carbon flux estimates. We are also interested in candidates who have experience applying machine learning to InSAR and other remote sensing