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Field
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applications in image analysis and machine learning, as well as in digital signal processing and acoustic imaging. There are about 20 Postdocs and PhD research fellows in the group with financing from a variety
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should possess: PhD/Ms/BSc in Computer Science, Artificial Intelligence, Electrical Engineering, or a related discipline. Strong research background in one or more of: Computer Vision Machine Learning Deep
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should have experience in real-time processing or FPGA-based prototyping or embedded sensing architectures, or machine-learning-driven analysis for photon-limited measurements. Exposure to event-driven
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analysis pipelines for Raman spectral classification, potentially integrating machine learning methods. Research & Project Responsibilities Plan and execute experimental workflows to achieve project
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at the intersection of marine ecology, ocean technology, machine learning, and high-throughput biological imaging. This position offers a rare opportunity to help pioneer the use of advanced shadowgraph imaging systems
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a new computational paradigm that combines the versatility of the digital computer with the efficiency of close-to-physics computing. The group targets the full computational stack, from materials
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Principal Investigator and a cell-culture specialist in a friendly, multidisciplinary group spanning optics, electrophysiology, microfabrication and machine learning, collaborating with partners
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field high-speed microscopic imaging Experience with control and synchronization of high-speed imaging and lighting systems Experience with image post-processing and data extraction Personal
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verbal, written communication skills In-depth knowledge of deep learning, specifically VLM models, computer vision techniques (e.g., open vocabulary object detection, model distillation, VQA, test-time
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Engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly analytical, proactive and a team player Excellent teamwork and verbal, written communication skills In-depth knowledge