82 programming-"the"-"DAAD"-"EURAXESS"-"Prof"-"U"-"UCL"-"U.S" Fellowship positions at Nanyang Technological University
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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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, 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
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Excellent publication track record on top tier conferences/journals Proficiency in programming language Python Excellent verbal and written communication skills We regret to inform that only shortlisted
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of programming languages such as matlab and Python. We regret to inform that only shortlisted candidates will be notified. Hiring Institution: NTU
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for educational uses Good hands-on experience in programming, e.g., C/C++/C#, CUDA, Python, and scripting Track record in research and publication particularly in education Strong knowledge and hands-on experience
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programming languages such as C and Python Proficiency in deep learning frameworks such as Pytorch and Tensorflow Knowledge in imaging and computing device and equipment Good written and oral
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communication, or signal processing. Proficiency in programming languages like Python, MATLAB, or C++, and experience with AI/ML frameworks like TensorFlow, PyTorch, or scikit-learn. A proven track record of