74 algorithm-development-"Multiple"-"Simons-Foundation"-"Prof"-"UNIS" positions at NEW YORK UNIVERSITY ABU DHABI
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upon cognitive development and decline. To achieve these objectives, research projects rely on genetically engineered mice models, behavioral analysis, molecular dissection, high-throughput sequencing
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Description The Center for Technology, Economics, and Development
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demonstrated expertise in synthetic organic chemistry, particularly in areas such as catalysis, methodology development, total synthesis of natural products, photoredox or electro-catalysis, and computational
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, artificial intelligence, computer vision, robotics, UAVs, etc. is a plus. Other preferred qualifications include: expertise in programming and coding (preferably using Python and C++) and GUI development
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on the evolution of Afro-Eurasian world economy during the ‘Bronze Age’ with a particular focus on Arabian desert and the Eurasian steppe outliers of the so-called ‘first civilizations’. We seek a candidate with
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Description The Water Research Center at New York University Abu Dhabi seeks to recruit a Post-Doctoral Associate to develop calix[n]arene-based covalent organic frameworks for water purification
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theory, visualizations, and online tool development. Experience in conducting online controlled experiments is also desired, but not required. Excellent communication skills in English, ability to work in
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candidate is expected to take a leading role in the development of the group tasks and help in supervising PhD students. Applicants must have a PhD in theoretical high energy physics or related field
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at leading international conferences. The PDA is expected to contribute to the intellectual property development through patent filings, as well as participating in standardization efforts relevant to wireless
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related to materials. The successful candidate will independently lead a project focused on developing generative AI models to establish structure-property relationships for materials discovery