423 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" research jobs in Singapore
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(specifically PCECs). Proven experience in developing and validating numerical models (e.g., using COMSOL). Hands-on experience with programming for numerical optimization, machine learning, and data processing
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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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high-impact publications. 2-year appointment, with potential for extension subject to performance and fund availability. Responsibilities Develop advanced statistical and machine learning modeling
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, building automation and control (BAC) system, Artificial Intelligence (AI) & Machine-Learning (ML) applications. Good written and oral communication skills Proficiency in power system modelling, advanced
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engineering or related field At least 1 year of relevant experience in signal processing and machine learning. Good written and oral communication skills Proficiency in ANSYS, and lab test skill Ability to work
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a Research Fellow to contribute to a project focused on focused on data-driven discovery of atomic catalysts. Key Responsibilities: Theoretical predictions using DFT and machine learning, and
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the area of efficient and interpretable machine learning systems. The successful candidate will work on projects involving ensemble learning, large-scale data analytics, and high-performance model design
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Computer Science, Artificial Intelligence, Data Science, Automation, Electronic Engineering, Economics, Human Resources Management, or a related field. Experience with general methods in machine learning, such as
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. • The ability to work independently and collaboratively within a multidisciplinary team. • Strong writing, critical thinking, communication, and presentation skills. • Experience in Machine Learning is a
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on the laboratory can be found here. Our group develops machine learning algorithms to automatically generate discoveries from large-scale brain imaging data. We aim to uncover fundamental principles