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The SigCom research group at SnT, led by Prof. Symeon Chatzinotas, focuses on wireless and satellite communications for future 6G networks. Research includes security, IoT, unmanned aerial vehicles
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and research network and is committed to recruiting high-quality academics and professionals to contribute to its dynamic, quality-driven research environment. About AITTC The Agricultural Innovation
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Science, Computer Engineering, Informatics, Data Science, Computational Social Science, or adjacent disciplines with research experience in agent-based modelling, social data science, or social network analysis and
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in the preparation of grant applications (as appropriate); And collaborate with scientists within the NYU Global Network and in Abu Dhabi. Training & professional development* Attend trainings and
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POTENT project, we are working with Living Lab Networks including academic and industrial partners and ports to accelerate the green energy transition by investigating the use of ports as energy hubs
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to grow by 20% by 2030, these challenges require a shift from isolated logistics operations to collaborative, connected logistics networks. Upcoming policy measures, including kilometre chargers, CO2 caps
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or fellowship Delivering lectures or seminars, which will be compensated at the end of each semester Attend 3 professional development workshops or training sessions per year Participate in at least 2 networking
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the backbone of NYU’s global network university, an interconnected network of portal campuses and academic centers across six continents that enable seamless international mobility of students and faculty in
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Dhabi, NYU New York, and NYU Shanghai, form the backbone of NYU?s global network university, an interconnected network of portal campuses and academic centers across six continents that enable seamless
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
learning. Our previous work has demonstrated that neural networks can skillfully predict sea ice data assimilation increments, which represent structural model errors (https://doi.org/10.1029/2023MS003757