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collaboratively with faculty, postdoctoral researchers, students, and other members of a multidisciplinary research team. Required Qualifications: Applicants must hold a PhD in Geotechnical Engineering or a closely
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possible research topics include: (i) social media analysis, (ii) collaboration and teamwork, (iii) gender inequality, (iv) diversity, (v) online controlled experiments, and (vi) network science. The ideal
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and intelligent vision systems, including efficient learning and inference of complex AI/ML algorithms, specialized neural processing hardware and design tools, and ML security, and their applications
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specific projects that the candidate would like to lead within CITIES, along with potential collaborators within the Center. If you have any questions, please email us at [email protected] . Evaluations
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-doctoral associate will spend half their time on independent research, and half their time on collaborative research with Professor Stéphane Helleringer. The collaborative research will be on population
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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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strong collaboration with the SHORES multidisciplinary research teams. The project will be focused on advanced modeling of coupled fracture/damage of geomechanical materials when subjected a range of