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on wind turbines and ships. This involves advanced computer vision, dedicated lighting systems, optical communication, and robust control and guidance algorithms. You will work on: Design and implement
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, reconstruction algorithms, and data acquisition techniques to ensure high-quality inputs. Collaborate with clinicians: Work with medical specialists to validate the clinical utility of your algorithms and ensure
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ultrasound physics, reconstruction algorithms, and data acquisition techniques to ensure high-quality inputs. Collaborate with clinicians: Work with medical specialists to validate the clinical utility of your
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deep learning algorithms. We welcome applications from individuals with experience in: Experience developing deep learning models for real-time image/video segmentation, object tracking, reinforcement
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algorithms that maximize the information extracted from images and delivered to the robot. To be successful in this role, we are looking for candidates to have the following skills and experience. We welcome
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well as collaborate with PhD candidates. You'll design experiments using our robotic platform, analyze tactile data patterns, implement real-time control algorithms, and validate performance across diverse scenarios
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new globally accessible infrastructure and new algorithms for multimodal mining of biosynthetic diversity, as well as novel lead compounds that can be taken up by consortium partners to attain concrete
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manufacturing technologies, including light-based (DLP) and extrusion-based (3D fiber deposition) approaches. You will take the lead on applied physics, mechanics, manufacturing processes, and algorithm/coding
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-time control algorithms, and validate performance across diverse scenarios. You'll be part of the Tactile Machines Lab, which is a dynamic, interdisciplinary group of researcher bringing together
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-guided medical applications, with a focus on advanced robotics. You will work directly with clinical data to design robust, efficient deep learning algorithms that maximize the information extracted from