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Field
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servicing missions. Experience with machine learning techniques for robotic decision-making and intelligent control for tasks with high uncertainties. Experience with research on multi-agent collaboration and
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. Publish high-quality research in top-tier conferences and journals. Job Requirement: Ph.D. in Computer Science, Robotics, or a related field. Expertise in machine learning and safe navigation algorithms
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/mathematical-cognition-and-literacy . The group collaborates with national and international experts in mathematical cognition, mathematics education, linguistics, and machine learning. Your immediate leader
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to assess potato dormancy break, including: data collection, processing, AI model development and classification accuracy assessment. Involved in supporting an electrophysiology-based machine learning model
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processing and machine learning, as well as, online control of assistive systems. The PhD position is located in Aalborg, and the candidate will be a member of Neurorehabilitation Systems group at the Health
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The fellow will be responsible for: Building collaborations with our multidisciplinary team (medical physicists, engineers, computer scientists, nuclear medicine physicians) to develop and implement innovative
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computer skills for accurate data collection using various hospital EMR systems (primarily EPIC systems) and willingness to learn various Data Capture systems (WebDCU, RAVE, Red-Cap) ability to work on site
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(Python, JavaScript), deep neural networks and computer vision; Design and implementation of database systems; Design and implementation of application programming interfaces, server-based and cloud
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scientists, nuclear medicine physicians) to develop and implement innovative AI algorithms applied to medical images To lead effort on enabling translational and physician-in-the-loop AI solutions for medical
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classification accuracy assessment. ii) Involved in supporting an electrophysiology-based machine learning model to predict dormancy break. You will be part of a multidisciplinary academic and industry team