73 parallel-and-distributed-computing-phd Postdoctoral positions in United Arab Emirates
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of the advertised topics, as well as an excellent academic record. Candidates with PhDs in Physics or Computer Science may also be considered if they willing to collaborate with mathematicians on these topics
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explore enabling technologies for 6G and beyond wireless networks. Applicants must hold a PhD degree in electrical/electronics engineering, telecommunications or related field. Other requirements include
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workflows in complex organizational settings. Qualifications: Applicants must have a PhD in Computer Science or related field. Experience in one or more ML domains, such as deep learning, reinforcement
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experimental data. Required Qualifications: A successful applicant must have a PhD in Engineering Mechanics, Civil Engineering, or Mechanical Engineering. Applicants are expected to demonstrate research
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-edge machine learning, including Large Language Models (LLMs), to enhance decision-making and planning in robotic systems. Qualifications: Applicants must have a PhD in Robotics, Control Theory
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newly established fluid dynamics laboratory at NYU Abu Dhabi, candidates are expected to have a strong interest in experimental research and collaborate with applied mathematicians closely. PhD holders
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Description As part of the Electrical Engineering program of the Engineering Division and the Center of Artificial Intelligence and Robotics at NYU Abu Dhabi the group of Prof. Kyriakopoulos seeks
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, cardiovascular, and neurologic diseases. These projects entail computational modeling, device design and manufacturing, optimization of chemical, mechanical, and electrical characteristics, and preclinical
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candidates will work in a multidisciplinary Center environment with world-class research infrastructure, consisting of PhD-level scientists, graduate students and undergraduate students. The terms
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apply. A PhD dissertation or research papers that demonstrate a strong interest and research focus in any of risk analysis or minimization, robust optimization, deep learning for systems, probabilistic