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, access state-of-the-art computational resources, and contribute to high-impact research that bridges academia and industry. If you have a strong background in AI, machine learning, and a keen interest in
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contributes to positive change in society. We are actively committed to a sustainable and climate-neutral university . You can expect numerous benefits , such as public transport season tickets and car sharing
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and climate-neutral university . You can expect numerous benefits , such as public transport season tickets and car sharing, a wide range of sports offered by the ASVZ , childcare and attractive
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team members Perform accelerated optical degradation tests of transparent conductive materials Apply machine learning techniques for data analysis and time-series forecasting Collaborate in a
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samples, sectioning, immunostaining Acquire a series of confocal microscopy images Quantify images using pre-defined algorithms Prepare GLP compliant reports Your profile Biologielaborant/in (or equivalent
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telescopes. Explore Machine Learning techniques (CNNs, DBSCAN, Transformers, etc.). Implement low-latency computing accelerators on FPGAs. Contribute to open-source ML-on-FPGA tools (e.g., HLS4ML, FINN
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progress Profile Required Master's degree in computer science (preferred), mechanical engineering or computational engineering Proficiency in Python programming Strong expertise in machine learning and deep
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for developing unmanned surface vehicles. The group's primary research areas encompass multi-agent system design and control, adaptation, machine learning, and physically embodied intelligence. In this dynamic
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these projects will bring forward the integration of novel methods at the intersection of advanced control, optimization, manufacturing science, robotics, and machine learning. The two doctoral student positions
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Geology or other related discipline Demonstrated expertise in machine learning and computer vision algorithms is necessary, with an emphasis on object tracking, optical flow and sensor fusion Knowledge