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and machine-learning algorithms for conflict detection, collision avoidance, flight-path planning, and rerouting under uncertain and dynamic maritime traffic conditions. Develop perception- and
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learning algorithms, including Federated Averaging and Federated Proximal methods, to collaboratively train machine learning models across distributed agents while preserving data privacy. Dynamic Task
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information from multimodal spatiotemporal data, including physiological signals, imagery, and natural language, via adaptive machine learning; 2) Personalization of sequential decision making
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position at the School of Science and Technology. Subject area The subject area for this position is Computer Science, with a focus on machine learning and signal processing applied to proprioceptive
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-Schnittstelle. Dein Profil Sehr guter Masterabschluss in Informatik, Robotik, Ingenieurwissenschaften (1,x-Schnitt) an einer anerkannten Universität Erfahrung mit Machine Learning / Deep Learning
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or other ML-based techniques for robot control is considered a plus. You have excellent computer science skills (python, git, linux, ROS, etc.) . You have hands-on experience with machine learning
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machine learning, wireless communications, signal processing, multimodal sensing, robotic perception, optimization, or control will be an advantage. The candidate should be comfortable with scientific
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a Machine Learning Research Scientist who will support the development of fundamentals for GeoAI imagery processing, self-supervised learning methods for large vision-language models to enable
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-doctoral researchers, visiting researchers, master's students, etc.) Research Context Recent advances in mobile robotics have been driven by remarkable progress in perception, deep learning, and control
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, Python, or Stata; experience with machine learning or advanced experimental methods is a plus) Familiarity with VR-related toolkits (e.g., Unity, Unreal, or eye tracking) is an advantage, especially for