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available single-cell sequencing data generated from patient samples and mouse models, we will enhance and apply machine-learning based algorithms to deconvolute bulk tumor RNA-seq samples to distinct immune
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, the next step in this project is to address sparse optimization for tensors. We propose the integration of randomized algorithms into sparse optimization frameworks for the purpose of completing
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data sources such as UK Biobank and eventually come up with algorithm useable for the early detection of Alzheimer’s disease (AD) and Parkinson’s disease (PD). Nature of Work: In this project, we will
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how innovation is integrated into patient care to improve clinical outcomes. Our current projects include developing wearable sensors and telehealth solutions to monitor physical and cognitive
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design, prototyping, testing, and refinement of robotic systems and automation solutions, including sensor integration and feedback control. Collaborate with a multidisciplinary team to design and execute
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motivated postdoctoral fellow to investigate how cell death sensors regulate immune responses, with an emerging interest in the retina. Building on our prior work (PMID: 35969037, PMID: 36662852) we aim
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University. The Center for Behavioral Science Research seeks a postdoctoral associate with strong interest and competency in mobile health (apps, text, sensors, VR) and health behavior change. The position is
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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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., adolescents, college students, STEM teachers, healthcare professionals) multimodal multichannel data (e.g., log files, eye-tracking, physiological sensors, facial expressions of emotions, screen recordings, etc
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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