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tensor network algorithm development and application. Competency with common scientific programming languages such as C++, Python, and/or Julia and version control systems. Experience in parallel
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18,500 people, including over 14,000 students and 4,000 researchers from more than 120 different countries. Post-doc on formal verification and algorithm discovery for numerical analysis About us and
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candidate for postdoctoral researcher position to conduct collaborative research aimed at the development of novel data mining algorithm to neuroimaging, genetic, and clinical data for brain disorders
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, computational biology, numerical analysis of partial differential equations (including ice and ocean dynamics), computational statistics and machine learning, as well as algorithm design and discrete
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independent and collaborative research in electromagnetic sensor systems, including theoretical analysis, numerical modeling, AI-assisted sensing algorithm development, and experimental validation
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independent and collaborative research in electromagnetic sensor systems, including theoretical analysis, numerical modeling, AI-assisted sensing algorithm development, and experimental validation
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independent and collaborative research in electromagnetic sensor systems, including theoretical analysis, numerical modeling, AI-assisted sensing algorithm development, and experimental validation
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evaluating their performance relative to classical machine learning and statistical methods. The research would combine algorithm development with implementation and evaluation on current quantum computers
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computational methods, working with large and heterogeneous datasets, evaluating algorithm performance and uncertainty, and translating research methods into reproducible scientific software and analyses. The
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focuses on algorithm development, data fusion, and deployment for anomaly detection in solar panels and battery systems. Key Responsibilities Develop computer vision and deep learning algorithms