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with vessel protected volume estimates to identify safety-buffer overlaps, developing multi-agent path-planning, and machine-learning methods for corridor allocation, airspace capacity optimisation, and
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. Interface with machine learning group on database set up CO2 removal process Job Requirements: PhD in Chemistry/Materials Science/Physics Candidates with strong background in Materials chemistry/Physical
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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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research in formal verification, machine learning and artificial intelligence system assurance. The successful candidate will develop new techniques and tools for analysing, verifying and improving
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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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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
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intelligence, machine learning, deep learning, environmental modelling, climate-health research, early warning systems, or related fields. Have strong programming and computational skills in Python, R, MATLAB
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maintain collaborative partnerships with faculty and staff across the institution, demonstrated through prior experience or a strong capacity and willingness to learn. Experience in and/or demonstrated
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verbal, written communication skills In-depth knowledge of deep learning, specifically VLM models, computer vision techniques (e.g., open vocabulary object detection, model distillation, VQA, test-time