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research aims to develop new AI for shared human-AI decision-making in healthcare imaging. This post focuses on bridging theory and applications of the Learning-to-Defer (L2D) framework, building on recent
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tools (photoelectron imaging and action spectroscopy) to study the structure and dynamics of transition metal complexes. The research project aims to develop a new method for elucidating the mechanisms
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Previous Job Job Title Post-Doctoral Associate Next Job Apply for Job Job ID 372669 Location Twin Cities Job Family Academic Full/Part Time Full-Time Regular/Temporary Regular Job Code 9546 Employee
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University of California Riverside School of Medicine | Riverside, California | United States | 6 days ago
contacting: aobenaus@medsch.ucr.edu We are recruiting for the following areas: Vascular physiology: This position will use modern in vivo imaging (miniscopes, 2-photon, magnetic resonance imaging
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monitoring, structural and functional magnetic resonance imaging, transcranial magnetic stimulation, and genomic assays. Duties involve research study design, participant recruitment, data collection, data
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systems for diagnostics and treatment. Core activities include signal processing, antenna design, and measurement hardware development. Building complete prototype systems for clinical testing is a central
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) participate in the monitoring at sea to acquire video and picture of the transplanted sites, (2) quantitatively analyse video to define species and functional diversity, species abundances and population size
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variability, whichincreasingly disrupts the operation of electrical circuits and reduces the design margin of the circuits (Fig. 1). This is particularly the case for the reading circuits of CMOS imager
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visualization; applicants are encouraged to include links to relevant code or repositories in their CV experience working with multimodal or data‑driven research workflows and translating quantitative outputs
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fundamental discovery to patient care. Our laboratory focuses on advanced label-free optical technologies for disease detection and characterisation. We develop fibre-optic and multimodal imaging systems