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Field
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areas: wireless security, wireless communications, AI/machine learning for communications, covert communications, signal processing, and/or RF design. Ability to conduct research independently and
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computer science. About the Group The Data Intelligence Group at UM6P-CC is a growing and supportive team with internationally recognized expertise in data management and machine learning. The group has a
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submitted. If email is not received, check the junk folder before contacting ORISE to confirm submission. To apply and learn more about EIF and host institutions – such as eligibility, requirements, and
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candidates using photometry, spectral energy distributions and, when available, spectroscopic data. Both fellows will produce diagnostic plots and summary tables. Simple statistical or machine-learning methods
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the NYUAD Kawader program, for details regarding the program, open dates, specific program requirements, and FAQ's please refer to our NYUAD Kawader webpage: https://nyuad.nyu.edu/en/about/careers
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methodologies. Additionally, CFD simulations combined with physics-informed machine learning will also be examined. Several research and industrial partners are a part of this project. The ideal candidate would
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degree in Computer Science/Computer Engineering. Possessing a Master’s or PhD degree will definitely be advantageous. Knowledge of machine learning, pytorch, huggingface etc... Knowledge of image
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relationships and apply data-driven or machine learning approaches to guide molecular design and accelerate materials discovery Collaborate with internal and external stakeholders, including computational, data
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welcoming campus community and we seek candidates whose research, teaching, and community engagement efforts contribute to robust learning and working environments for all students, staff, and faculty. We
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learning or computer vision libraries; familiarity with Vision-Language Models (e.g., CLIP, BLIP) or scene-graph inference is a plus. Key Competencies Strong software development and debugging skills. Able