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Field
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collaboration by proposing an original hybrid rule-driven/data driven approach to artificial intelligence and by studying efficient optimization algorithms. The team focus on robotic applications like environment
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us. II. Positions and Requirements Position 1: Scientist in Intelligent Biobreeding Algorithm Responsibilities: Lead the formation and direction of an interdisciplinary team to integrate AI
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autonomy, we need teamwork: nearby vehicles, drones, and roadside units must co-perceive their environment, sharing and fusing complementary sensor views in real time. Yet raw video and point-cloud streams
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and algorithm design Acquire detailed knowledge in navigation sensor and systems technology Additional responsibilities for higher level position includes: Lead the design, development, testing
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intelligence. You have worked with tools, techniques, algorithms, software, and programming languages for deep learning, reinforcement learning, statistics, sensors and sensor fusion, planning, computer vision
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Max Planck Institute for Intelligent Systems, Tübingen, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | 7 days ago
algorithms to estimate human shape and motion in images, videos and RGB-D sequences. Our approaches define the current state of the art, and we are constantly pushing these methods and systems in order to
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‑loop controllers (e.g., roll, pitch, yaw); Develop and modify simulation models for flight‑control and autonomy assessment and use them to prototype, test, and refine control‑law algorithms; Design
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drone detection and localisation performance using radar systems. This can be achieved by improving the detection performance of individual sensors and by employing a cooperative network of sensors which
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length scales Develop machine learning algorithms to support process optimization, predictive modeling, and intelligent manufacturing control Integrate simulation tools with in-situ sensor data from
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with UAVs for tackling wildfires, including modular, scalable methods with respect to the volume of collected data, to the number of UAVs, data sampling rates, number of sensors, centralised