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ability to work independently and facilitate projects with minimal supervision. Able to contribute to Journal/Conference papers with good presentation skills. Able to plan and organize well and adhere
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applications, plant-based bio-material applications, etc. We are looking to hire a Research Fellow. Key Responsibilities: The primary objective will be plan, monitor, and perform experiments within the scope
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to Journal/Conference papers with good presentation skills. Able to plan and organize well and adhere to deadlines We regret to inform that only shortlisted candidates will be notified. Hiring Institution: NTU
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framework such as Tensorflow, Pytorch, MXNet and Programming Languages such as Python, Matlab, R and/or C/C++. Demonstrated project experience related to causal inference will be an advantage. Good written
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of nanomaterials. Programme and manage research activities, including experimental design, data analysis, and interpretation, ensuring alignment with project goals and timelines. Develop and implement machine
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, or a related field. Expertise in deep learning, multimodal LLMs, and Vision-Language-Action models. Strong programming skills in Python, with significant experience in PyTorch. Hands-on experience with
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, MAVLink). Hands-on experience with communication systems (e.g., Wi-Fi mesh, 4G/5G, UWB). Familiarity with swarm algorithms and real-time control systems is highly desirable. Strong programming skills in C
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. Requirements: PhD degree in statistics or a related field from a reputable university. Solid knowledge in hypothesis testing and high-dimensional analysis. Strong proficiency in the R programming language
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. Perform any other duties relevant to the research programme. Job Requirements: PhD in Computer Engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly analytical, proactive
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part of the Smart Gripper for Soft Robotics program. The program aims to deliver soft active gripper for manipulation of objects for industry applications. The design of coating, materials preparation