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of personal background, because we believe diverse perspectives and experiences improve research, support collaboration, and deepen our shared engagement with society. Qualifications Applicants must hold a PhD
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. The following experience will strengthen your application: industrial product development or manufacturing research modelling and simulation, digital twins or digital threads AI, machine learning
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, drawing on machine learning where it strengthens these methods. The research supports mission-critical scenarios and feeds into an end-to-end resilience proof of concept developed together with Swedish and
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, drawing on machine learning where it strengthens these methods. The research supports mission-critical scenarios and feeds into an end-to-end resilience proof of concept developed together with Swedish and
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related areas. Learn more: Our benefits , where we prioritize your well-being and success to enhance every aspect of your life. Being a part of the University at Buffalo community. As an Equal Opportunity
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analysis, GIS, and large environmental datasets Experience developing predictive or machine learning models for environmental systems Demonstrated record of peer-reviewed publications Experience
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are excited by fundamental mathematical questions motivated by real-world scientific and technological challenges. You have: A PhD in Mathematics or a closely related field. A strong research background in one
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to the development of remote sensing algorithms, simulation and modeling capabilities, and artificial intelligence/machine learning (AI/ML) methods in support of the goals of the joint NASA/USGS Landsat mission
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domains such as telecom, defence and cloud. You will join the Machine-Intelligence for Networks and Distributed Systems (MINDS) research group at the Department of Computing and Learning Systems, School
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submitting your CV and a separate cover letter (no more than 2 pages) that demonstrates how you meet the following selection criteria: PhD in Materials Engineering, Chemical Engineering, or a related