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Science, Mathematics, Physics, Bioinformatics, or a related quantitative field Strong background and expertise in data science, bioinformatics, network science, artificial intelligence, machine learning, deep learning
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. Responsibilities of the position include using advanced statistical and Machine Learning techniques to study AGN properties, galaxy properties, and the relationships between them in large samples of galaxies, as
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and development of particle detectors, including simulation tools such as GEANT4 is preferred, as well as enthusiasm to learn new techniques and to work and interact within a very diverse environment
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Post-Doctoral Associate in the Division of Engineering (Mechanical Engineering) - Dr. Mohammed Daqaq
to applicants with expertise in machine learning, wave propagation, metamaterials, and/or fluid–structure interactions. Applicants must hold a Ph.D. in Mechanical Engineering or a closely related discipline, with
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collaboratively within a team. Applicants must have a PhD, or equivalent advanced or terminal degree from a recognized institution of higher learning, in materials science and engineering, chemical engineering, or
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must possess substantial experience in artificial intelligence and machine learning methods, specifically in AI-driven materials discovery, machine learning applications for materials, or generative AI
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main PhD focus) such as additive manufacturing, advanced/hybrid manufacturing, machine learning, artificial intelligence, computer vision, robotics, UAVs, etc. is a plus. Other preferred qualifications
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and staff. Application Instructions NYUAD is being supported by the executive search firm Perrett Laver. For nominations or to learn more, please contact [email protected] . Formal applications