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, researchers, PhD students and analysts. We are known for our expertise on animal breeding, biological understanding of traits of cattle, swine, poultry and fish and sensor technology and big data analyses. We
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and waterscapes, through a.o. deployment of a range of smart participatory science approaches (e.g. citizen observations, cheap sensor deployment) together with local water users, water owners
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Delft explores AI-driven methods to enhance closed-loop simulation for safety-critical scenarios. A key focus is developing learned simulators that generate radar and lidar data from camera sensors
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welded joint. The main goal of these tests is to assess the fatigue strength and remaining fatigue lifetime after repair. During the tests you will monitor fatigue damage development with different sensors
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to conferences and professional networking opportunities. Job requirements MSc degree in Electrical Engineering or a related field Strong background in signal processing and its application to radar systems
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strong academic record with a solid background in Machine Learning (Deep Learning, generative models, diffusion models). Knowledge in sensor data processing and radaris a plus. Good programming skills