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Field
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Regularization. We aim to develop mathematical understanding of implicit regularisation properties in deep neural networks to guide the development of algorithmic paradigms aimed at combining statistical
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verification algorithms and prototypes on large microgrids, Naval systems, and utility systems. ● Assist grant proposal writing, work collaboratively with industry and government, and mentor graduate
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, or the design of efficient, explainable, and scalable query engines. The successful applicant will help design and build novel systems and algorithms that challenge traditional assumptions in databases, guided by
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research team working at the intersection of machine learning, algorithmic fairness, human-computer interaction, and responsible AI. The project aims to investigate how bias emerges in data pipelines and AI
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Are you passionate about mathematical control theory and its applications? Are you eager to develop estimation and control algorithms for large-scale dynamical systems with the aim of making next
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This position focuses on the research and development of novel radiation detectors and associated edge-computing circuits and algorithms for X-ray, particle, and nuclear physics experiments
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on developing and analyzing algorithms, building reproducible computational studies, and disseminating results in leading venues. The position collaborates with faculty, students, and external partners
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academic research lab environment -Software programming for scientific simulations -Interdisciplinary and multi-physics relevant strong background -Design of computational algorithms for 1st /2nd order time
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genome science, including the development of new algorithms and statistical methods to analyse genome sequencing data. Moving forward, the labs are jointly building an interdisciplinary research team
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AI Algorithm and Autonomous Decision-Making Systems RESPONSIBILITIES Research and develop autonomous decision-making algorithms for process industries (e.g., chemical, pharmaceutical, materials