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-solving skills. Team player with good communication skills. Proficiency in English. For consideration, applicants need to submit a cover letter, curriculum vitae with full publication list, statement
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algorithmic perspectives on large language models Statistical learning theory and complexity analysis Automated theorem proving and formal methods Random matrix theory and its applications in modern AI systems
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learning, or human-centered ML. Proficiency in programming languages (e.g., Python) and ML frameworks (e.g., TensorFlow, PyTorch), with evidence in the form of public (Github) repository. Excellent abilities
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engineering, computer science, urban science, or a related field. Experience in transportation, in particular related to urban science is required. Additionally, excellent communication skills in English and
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design and fabrication, electronics, chemical coatings, and in vitro and in vivo experimentation) are required. Proficiency in English is required. For consideration, applicants need to submit a cover
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decision process for innovation, collecting neurophysiological and other relevant data, programming and analysis routines, as well as quantitatively analyzing the data collected. Candidates must hold a PhD
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robotic platforms. A strong publication record in high-impact journals and conferences (e.g., T-RO, IJRR, RA-L, RAS, IROS, ICRA, CDC, etc.), showcasing your expertise. Proficiency in programming languages
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communication theory, signal processing, machine learning, and optimization theory. Strong verbal and written skills in English. Excellent analytical and problem-solving skills, and capacity to pursue independent
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of publications in relevant IEEE journals and conferences, Strong verbal and written skills in English, Excellent analytical and problem-solving skills and capacity to pursue independent research. In
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research environment. About NYUAD: NYU Abu Dhabi is a degree-granting research university with a fully integrated liberal arts and science undergraduate program in the Arts, Sciences, Social Sciences