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Field
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or image processing Experience with AI-assisted or feedback-driven fabrication workflows Interest in quantum photonic platforms, electro-optic systems, or light–matter coupling physics Application Materials
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, surrogate modeling of scientific processes, workflow automation and adaptive simulation pipelines, and performance analysis and optimization. The candidate will also contribute to and help originate research
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artificial intelligence with a preferred focus on computer vision and medical image analysis. Preferred Qualifications: PhD in Medical Physics, Bioengineering, Biomedical Engineering, Physics, Computer Science
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computed tomography (CT) reconstruction, including sparse-view and limited-angle algorithms, and the application of advanced machine learning (ML) and computational imaging methods to scientific and
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protected and open field cultivation systems Use lab and field equipment (ICP, HPLC, gas exchange analyzer, soil/root/plant sensors, chlorophyll fluorescence, etc.), data loggers and image processing tools
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be organized in accordance with the applicants’ interests and expertise, but will broadly be related to the neural mechanisms underlying the cognitive control of movement and non-motor processes
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a novel multi-omics approach that integrates high-throughput imaging and machine learning methods with CRISPR/Cas9 screens and saturation mutagenesis to answer central questions about the
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analytical processes for comparing traditional and AI-augmented analysis Build infrastructure for capturing observable traces of human-AI analytical interactions Develop tools and metrics to quantify accuracy
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and technical gaps that prevent fundraising. Our goal is simple: Make your start-up investable by empowering participants to mature their ideas from concept to prototype to first commercial product
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Current Employees: If you are a current Staff, Faculty or Temporary employee at the University of Miami, please click here to log in to Workday to use the internal application process. To learn how