160 phd-computational-"IMPRS-ML"-"IMPRS-ML"-"IMPRS-ML" positions in United Arab Emirates
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work in a multidisciplinary environment consisting of PhD-level scientists, research engineers, graduate research students and undergraduate students, to investigate cutting-edge scientific methods and
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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 The NYU Abu Dhabi Humanities Research Fellowship for the Study of the Arab World program invites applications for its upcoming Graduate Student Research Workshop to be hosted on February
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innovation in every year of the curriculum: students enjoy a learning environment conducive to creativity, which is at the heart of tomorrow’s technological innovations. Graduate programs - Global PhD
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28 Aug 2025 Job Information Organisation/Company NEW YORK UNIVERSITY ABU DHABI Research Field Literature Economics Engineering Computer science Mathematics Researcher Profile Recognised Researcher
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Platforms and High-Performance Computing facilities. Principal responsibilities of a Research Assistant include conducting experiments to understand the molecular mechanism of m6A readers on synapses through
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United Arab Emirates Application Deadline 10 Oct 2025 - 00:00 (UTC) Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU
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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