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Field
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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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reconstruction algorithms that incorporate multiply-beam coherent scattering imaging in a grazing incidence geometry to improve the spatial resolution to ultimately demonstrate the utility of the novel coherent
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the possibility of yearly renewal subject to funding availability. Responsibilities • Design and implement deep learning architectures, AI agent pipelines, and computer vision algorithms to achieve project goals
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 7 hours ago
/or machine learning/artificial intelligence algorithms. Projects may also include work focused on the analysis of spatial and geographic data and work extrapolating results to different spatial scales
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degrees of knee flexion and retreat to neutral position of the ankle. The system must be lightweight, affordable, and adaptive. Furthermore, the system will be equipped with force sensors embedded in
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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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multiscale simulation methods for quantum mechanical properties of macromolecules, developing novel ways to combine quantum chemical methods and machine learning, developing quantum algorithms
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Pharmaceutical health outcomes, (Pharmaco)epidemiology, Biostatistics, or a related field. · Expertise in or a strong interest in machine learning and deep learning algorithms. · Excellent communication skills
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models for fracture propagation, reactive transport, and reservoir-scale hydrogen yield prediction. Design and implement data acquisition systems and sensor integration for experimental campaigns. Prepare
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Spectroscopy (dwSCOS) sensor for non-invasive microvascular monitoring. 2. Perform Monte Carlo simulations for optical modeling of photon propagation in layered tissues. 3. Fabricate and characterize dynamic