441 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" "U.S" research jobs in Singapore
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Job Description Job Alerts Link Apply now Research Analyst/ Associate/ Fellow in Machine Learning and Artificial Intelligence (ML/AI) University-Level Unit: Sustainable and Green Finance Institute
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to conduct research in the areas of safety-critical control theory and machine learning. The role will focus on combining new theory or method in nonlinear system control and state-of-the-art machine learning
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Engineering, or related field. Research experience with Artificial Intelligence/Machine Learning/Large Language Model. Publication track record in a series of top tier conference papers e..g, in NeuRIPS, ICLR
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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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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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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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advance research in computer vision, machine learning, and/or robotics for the digitalization, monitoring, and automation of civil infrastructure. The role will focus on developing innovative methodologies
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/Research Fellow(SRF/RF) to carry out research in robotics and machine learning by exploring cutting-edge approaches such as learning-based robot perception, adaptive control with reinforcement learning
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students. Job Requirements: A Bachelor’s degree in relevant fields with past experience in embedded system, machine learning and software development. Knowledge in robotic system development is a plus
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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