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Yale Analog and RF Circuits and Systems (ARCS) Research Group, Department of Electrical and Computer Engineering, Yale University The Analog and RF Circuits and Systems Research Group in
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) at Argonne National Laboratory to advance learning-enabled imaging methods. This position offers a unique opportunity for candidates with backgrounds in electrical engineering, computer science, applied
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setting with access to state-of-the-art imaging, electrophysiology, and computational resources. The Kumar Lab is committed to fostering scientific excellence, collaboration, and the professional
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an advantage Strong background in machine learning for image analysis and computer vision, ideally involving microscopy, time-lapse imaging, or other high-dimensional scientific imaging modalities
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professional audiences strong planning and organisational skills with the ability to manage competing priorities proficiency in computer applications and research-related systems. Sponsorship / work rights for
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(Midavaine et al., Science, 2025). Building on this foundation, the lab combines mouse genetics, single-cell and spatial transcriptomics, in vivo calcium imaging, sensory behavioral assays, and molecular
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phenomena in low-dimensional systems. The materials studied will include superconductors relevant to quantum information science as well as unconventional and candidate topological superconductors and
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vision, controls, cyber-physical systems and their security, hardware security, and machine learning and their security. The work will include algorithm design, prototype implementation (e.g., in Matlab
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aspects of informatics and advanced data analysis. You will be responsible for Conceptualise and design experiments Undertake and drive a research project with view to publication Help supervise other lab
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for executing statistical and computational research activities focused on novel methods development for processing, segmentation, and trait extraction from 3D CT images of plant roots under the mentorship and