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(DFT) simulations and develop machine learning potentials to investigate zeolite-related systems. The role will focus on delivering research projects and promoting research excellence in this area. The
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Synthesis Strong background in materials formulations or synthesis Experience in printing technology or coating techniques Expertise in Actuator device fabrication Expertise in AI and machine learning is
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or thermal properties Expertise in AI and machine learning is advantageous Excellent written and verbal communication skills Ability to work independently and as part of a team We regret to inform that only
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of wireless communications, edge computing, and machine learning, and who is eager to translate theoretical insights into practical systems. Key Responsibilities Derive and analyse closed-form mathematical
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, procurement, or grant administration will be an added advantage. Experience in areas such as Machine Learning, Deep Learning, Computer Vision, Large Language Models, Data Analytics, or Intelligent Systems will
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should possess: PhD/Ms/BSc in Computer Science, Artificial Intelligence, Electrical Engineering, or a related discipline. Strong research background in one or more of: Computer Vision Machine Learning Deep
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machine learning frameworks. Proficient in technical writing and system documentation. Self-directed learner with strong problem-solving and research capability. Where to apply Website https
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recognition elements. Experience applying machine learning to spectral data (Raman, LC–MS, or similar). Experience working on translational or industry-linked research projects. Where to apply Website https
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operation and maintenance of equipment Job Requirement Have relevant competence in the areas of Deep Learning/Computer Vision. The experience in diffusion models is a plus. Have a PhD degree in computer
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at NTU are looking for a Research Fellow (RF) to carry out research in probabilistic machine learning and GenAI, by exploring cutting-edge approaches such as sequence model design, continual learning