298 machine-learning "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" "UCL" Fellowship positions in Singapore
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or electrochemical system PhD in Chemistry/Materials Science/Physics Encourage initiating activities on MOF development, devising, and analytical process Experience in machine learning will be preferred Good oral and
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international work environment Learn more about CQT at https://www.cqt.sg/ Job Description The successful candidate will drive research at the intersection of Condensed Matter Theory, Quantum Computing and
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to groom the next generation of leaders, thinkers, 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
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focusing on the integration of machine learning, wafer-scale synthesis of materials. The role will contribute to the university's research mission by conducting fundamental research, helping secure external
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Engineering, Mechatronics, Computer Science, etc. Strong background in AI, Vision Language Model, end-to-end autonomous driving, deep learning, computer vision, robotics and automation. Candidates having
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Proficiency in ionic liquid handling and techniques Excellent written and verbal communication skills Ability to work independently and as part of a team Experience with machine learning in engineering is
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Research Fellow / Associate Research Fellow / Senior Analyst / Research Analyst (Military Studies Programme) The S. Rajaratnam School of International Studies (RSIS), a Graduate School of Nanyang
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learning and development Proficient in technical writing and presentation Possess strong analytical and critical thinking skills Show strong initiative and take ownership of work Where to apply Website https
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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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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