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Models with Algorithmic Reasoning Tasks We are seeking a postdoctoral researcher to contribute to our lab’s mission of aligning machine learning (ML) models with algorithmic reasoning tasks. Our goal is to
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genetic knockouts in yeast and mammalian cell lines, and protein purification. Job Responsibilities: 35%: Computational algorithm development and data analysis 35%: Design and conduct experiments with yeast
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trustworthy medical AI? Deep models already outperform humans on many benchmarks, yet in the clinic they remain black boxes: radiologists cannot see why an algorithm flags a lesion, and AI engineers cannot tell
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- conducting processors with respect to practical short-depth (NISQ) quantum algorithms Cooperate and actively work with experimental partners developing quantum processors using these technological platforms
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Description The Quantum Information team at UMass Amherst is involved with modeling and optimization of quantum hardware, as well as development of new modeling methods and algorithms, in collaboration with
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interdisciplinary teams to apply developed algorithms to real-world datasets and generate valuable biological insights. Perform integrative analyses of multidimensional datasets within the context of basic immunology
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, Dental Materials, Dental Technology or a related discipline, with research experience in Non-linear Finite Element Analysis, CAD for dental prostheses, AI algorithm development using python / PyTorch, and
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models for signal transmission and reception, derivation of fundamental performance limits, algorithmic-level system design, and performance evaluation through computer simulations and/or experimental
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of performance limits, algorithmic-level system design and performance evaluation via computer simulations and/or experimental means. The PDA is expected to actively disseminate results through publications in
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algorithms. The research focuses on wind energy applications, creating a compelling sustainability narrative: developing more efficient computational methods to optimize wind farm performance, which in turn