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The research will address key challenges and explore the following areas: 1. Decentralized Scheduling Algorithms: Design algorithms for operational scheduling and rescheduling of shared assets in connected
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low-resource settings. This position is jointly supervised by Prof. Teun Bousema (malaria epidemiology) and Dr. Felix Hol (vector biology), ensuring strong scientific guidance across disciplines. It
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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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eligible for a tax exemption on a part of their salary during the first five years in the Netherlands. Selection process For more information about this position, please contact Prof. Johan van Leeuwen
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Do you recognize yourself in this profile and would you like to know more? Please contact dr. Chengmin Li (c.li7@tue.nl ), Prof. George Papafotiou (g.papafotiou@tue.nl ). Visit our website for more
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of their salary during the first five years in the Netherlands. Do you want more information? For more information about the position, please contact Prof. Maarten Schutyser, Full Professor, via email
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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