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computational chemistry, reaction network analysis, and machine learning for organometallic catalytic reactions. 2. Design of membrane-permeable macrocyclic peptide drugs via machine learning structure
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epitaxy (MBE) Develop innovative approaches to accelerate MBE materials development using in situ characterization & machine learning Integrate epitaxial synthesis with exfoliated two-dimensional materials
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++. Demonstrable experience with machine learning frameworks (e.g., PyTorch, TensorFlow). Hands-on experience with game AI agents and/or GUI agents such as Mineflayer, Unity ML-Agents, or similar. Solid expertise in
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computational electromagnetics and electromagnetic simulation techniques. Experience in AI-based RF transistor modelling is highly desirable. Solid knowledge of machine learning algorithms and their application
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systems, advanced sensing technologies, application of deep learning and AI for wireless systems, etc. For more details, please view: https://www.ntu.edu.sg/eee We invite applications for the position
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enhancing the use of effective applications and services for teaching and learning. We drive a culture that is forward-looking. With a strong passion for IT, our people are always striving to improve, push
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, machine learning, and life cycle assessment, we aim to create sustainable wearable systems to enhance human well-being. For more details, please view https://www.ntu.edu.sg/mse/research . We are seeking a
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schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . We are looking to hire a research fellow (postdoc) to undertake a project to develop efficient AI and Machine
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the Job related to staff position within a Research Infrastructure? No Offer Description Introduction As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our
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to staff position within a Research Infrastructure? No Offer Description As a University of Applied Learning, the Singapore Institute of Technology (SIT) works closely with industry in its research