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for the physical sciences. We have a strong profile in computational statistics, simulation and learning algorithms, and scientific software development. As a closely collaborating, international team
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Student assistant (m/f/d)-Multi-Modal Sensor Fusion, Object Detection in Clutter and Object Tracking
an automated evaluation pipeline. Calibrate and time-synchronize multi-camera systems with tactile sensors; define data schemas and ROS 2/Isaac ROS interfaces. Algorithm Implementation: Develop multi
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integrate data, develop novel algorithms/methods and provide quality assurance for this work Independently manage and coordinate research projects on the above-mentioned topics and independently acquire third
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documenting algorithms High degree of proficiency in spoken and written English What you can expect Fascinating challenges in a scientific and entrepreneurial setting Attractive salary Modern and excellently
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Max Planck Computing and Data Facility (MPCDF), Garching | Garching an der Alz, Bayern | Germany | about 2 months ago
workflows Deep understanding of machine learning algorithms and modern deep learning fundamentals Excellent programming skills in Python and PyTorch Practical experience with transformer architectures and
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with the latest sensors (camera and LiDAR sensors), is available for the work. What you will do Development of algorithms for 3D multi-object tracking based on heterogeneous sensor data fusion (standard
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and/or statistical algorithms to classify building and land-use types relevant to electrical consumption Label and prepare training data for AI models; develop automated pipelines for classification
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processing Simulation and verification of the implemented algorithms with test vectors Integration of IP cores into an OFDM-based Physical Layer Debugging of implemented designs in a LiFi testbed Collaboration
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to develop automated algorithms for downscaling drivetrain components for specific test purposes. Furthermore, you will perform multiple case studies to analyze the performance of the developed scaling methods
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will work in a group with other students and take on specific tasks. The aim is to analyse the robot's capabilities and to implement algorithms that enable the robot to be used sensibly in applications