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of state voting legislation for the Voting Laws Roundup. This work includes developing computational tools (e.g., using large language models, machine learning for text analysis and classification, etc
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geometric understanding of training in deep neural networks. The position offers excellent training opportunities at the intersection of machine learning and applied mathematics. Qualifications: - Applicants
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with biological tissue. Duties of the position will include designing optical spectroscopic imaging technology, using numerical simulation and machine learning tools to extract diagnostically-relevant
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, the Associate will assist with research and development projects in the areas of robotics, machine learning, control systems, and/or computer vision. They will be responsible for: designing and analyzing
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a position combining project management, machine-learning model development, data management/analysis, and manuscript writing for publication. Preference will be given to applicants with (1
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within the Academy for Teaching and Learning (ATL) by playing a key role in fostering Artificial Intelligence (AI) and emerging teaching and learning technology literacy among University faculty
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. Experience in machine learning methods is also required. Additionally, it is critical that the individual has experience in working with epilepsy patients, data collection via the NeuraLynx iEEG system, data
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Engineering or related field by the start date with expertise in optical diagnostics, high-speed or multiphase flows, and flow physics. Experience in laser-based velocimetry, data processing, and machine
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approach to develop chemical probes, investigate biological mechanisms, and evaluate in vivo efficacy. In particular we use the promiscuous pregnane X receptor (PXR) and constitutive androstane receptor (CAR
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. In particular we use the promiscuous pregnane X receptor (PXR) and constitutive androstane receptor (CAR) as models. PXR and CAR transcriptionally regulate cytochrome P450 3A4 (CYP3A4) and CYP3A5-drug