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, Biomedical Science and Technology, and 1500 students in our bachelors and masters programmes. We hold state of the art research and we offer state of art learning opportunities in our teaching facilities
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Biological Learning Machine, which is headed by Professor Jan Østergaard. The goal is to develop novel information-theoretic methods for identifying and analyzing temporal and spatial patterns of synergy and
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equivalent to a two-year master's degree in mathematics, physics, computer science, electrical engineering or closely related fields with a focus on computer vision, machine learning or robotics A strong
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and Computer Vision Excellent programmer in Java / C / Python or equivalent Excellent at using Machine Learning software, e.g. PyTorch / TensorFlow / Scikit Learn Highly knowledgeable in mathematical
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with expertise in digital signal processing methods, and machine learning methods for amplitude and phase noise characterization of optical frequency combs, recovery of dual-comb measurement signals and
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photonics or electrical engineering or applied physics or similar. Experience with machine learning, digital signal processing and experimental work is a plus. Further obligations: The doctoral candidate (DC
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mass spectrometry and machine learning now allow us to unravel this “dark proteome.” This position aims to use state-of-the-art AI-guided proteomics and systems biology approaches to map protease
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Compression of quantum data under unreliable entanglement assistance Joint compression and error correction for robust communication in the quantum-classical internet Quantum embeddings for machine learning
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knowledge of adaptive control, machine learning and AI. But the most important qualification is an eagerness to learn the mysteries of fuel-combustion-engine interaction. You must have a two-year master's
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Job Description If you are ambitious and interested in joining a supportive and dynamic research team working with Operations Research and Machine Learning on an important application look no