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Generative AI, Foundation Models, and related AI techniques. Developing and maintaining course content, exercises, and hands-on projects aligned with the latest research and industry practices. Fostering
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frameworks such as PyTorch, preparing them for advanced AI studies. Responsibilities include: Delivering high-quality instruction in Deep Learning and related AI subjects. Developing and updating course
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topics Developing and updating course materials, assessments, and lab exercises to reflect current advances in NLP and AI Fostering an engaging and inclusive learning environment that promotes active
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development of cognitive omni-band wireless systems for 6G and beyond. The successful candidate will be jointly supervised by Mahmoud Rasras and Murat Uysal and will work in close collaboration with other
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Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
management. Develop and validate computational models for monitoring and predicting infrastructure performance. Collaborate with faculty and researchers across SHORES. Disseminate research findings through
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opportunity to shape a dynamic academic division at a pivotal moment in the university’s evolution. The Dean will lead a vibrant community of scholars who advance foundational and applied research on some of
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the research team of Prof. M. Umar B. Niazi. The position focuses on the development of digital twins using physics-informed learning approaches, with specific applications to intelligent transportation
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environments, hardware platforms, and frequency bands Develop, validate, and document ISAC channel modeling methodologies tailored to the lab’s hardware/software testbed. Integrate SDRs (e.g., USRPs, RFSoC) and
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. The successful candidate will contribute to high-quality instruction, mentor graduate students, shape curriculum development, and engage in interdisciplinary research at the intersection of statistics, data
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candidate will be involved in cutting-edge research and development in 3D computer vision and machine learning for the digital preservation of cultural heritage. The project focuses on state-of-the-art