224 machine-learning-phd Fellowship positions at Nanyang Technological University in Singapore
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successful candidate should possess at least a PhD or Master degree in a relevant field and possess aptitude, interest and commitment for in-depth research, able to work independently, fluent in English with
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communication under mobility. Key Responsibilities: Research and Development: Design, develop, and evaluate AI/ML algorithms for autonomous automotive applications, focusing on online learning techniques with
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research articles to disseminate study findings Undertake project administrations and liaison Provide regular updates and reports Job Requirements: Possess a recognized PhD degree in Mechanical/Environmental
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preparation for high-impact journals. Job Requirements: PhD in Biochemistry, Molecular Biology, Synthetic Biology, or a related field (completed or near completion). Strong expertise in molecular cloning
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: A PhD degree in material sciences or applied physics, with focus on renewable energy Evidenced experience in synthesis of atomic catalysts or other catalytic nanomaterials for energy conversion
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opportunities through grant proposals Job Requirements: PhD in Electrical/Mechanical/Biomedical Engineering or relevant specialty Experience (3+ years) in a bioengineering specialty such as but not limited
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modeling, process design, process optimization, and machine learning in energy, environmental, and chemical processes. During his research career, Dr. Nguyen has authored more than 20 scientific papers, with
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journals and present at international conferences. Contribute to the mentoring and guidance of junior researchers and students, fostering an environment of learning and innovation within the project team
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for multiple-CPU and/or GPU platforms via parallelization schemes. Validating these codes via canonical and real-world examples. Job Requirements: PhD in Electrical and Electronic Engineering, Applied
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written communication skills in English for research work Preferred Requirements: Experience with deep learning and reinforcement learning algorithms in robotic decision. Familiar with UAV kinematics and