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strategy, the processing of sensor data (laserscans, images, pressure, etc.), as well as the reactive control of robotic arms. In order to apply for this position, the candidate should possess in-depth
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areas: scientific programming and data analysis (e.g., Python, R, C++, MATLAB), computational modeling, imaging and sensor data processing, bioinformatics, systems biology, or biophysics Familiarity with
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high-resolution, quantitative time-lapse soil property measurements using high-performance, parallel computing. Together with our existing rich dataset, we will inform a soil-plant digital twin, enabling
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computing. Together with our existing rich dataset, we will inform a soil-plant digital twin, enabling ML-based analysis of geophysical and rover approaches for field-scale root and soil characterization. You
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the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission analysis, and infrared thermography
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data analysis (e.g., Python, R, C++, MATLAB), computational modeling, imaging and sensor data processing, bioinformatics, systems biology, or biophysics. Familiarity with simulation environments
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one of the following areas: scientific programming and data analysis (e.g., Python, R, C++, MATLAB), computational modeling, imaging and sensor data processing, bioinformatics, systems biology, or
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into an interdisciplinary research environment given by the university institutes and the cooperation partners in industry and science. The advanced Manufacturing Engineering paradigm for next generation factories is
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partner from data sciences provides data management and AI based Image analysis, an internal experimental group, and an internal simulation-sciences group (You+Supervisor+support by lab
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electrode structures. • Prototyping of the identified structures via stereolithographic 3D printing and advanced textile techniques. • Development of advanced imaging and characterization technologies (X-ray