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, HHU Düsseldorf). Prof. Amunts is a leading expert in brain mapping and the development of human brain atlases at microscopic scale. Her group pioneered the Julich-Brain and BigBrain projects using deep
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computing. These include computer graphics and geometry processing, computer vision and image processing, visualization and visual analytics, augmented and virtual reality, machine learning and deep learning
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/phd-in-micromechanical-experime… Requirements Specific Requirements An outstanding, motivated, enthusiastic, curiosity-driven researcher. Deep analytical skills, initiative, creativity, and flexibility
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for a candidate with: an MSc in computer science, artificial intelligence or a related field a creative and collaborative mindset strong programming skills in Python or Rust strong skills in deep learning
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deep learning into practical tools for sustainable urban energy systems, supporting applications in forecasting, system optimization, flexibility management, and resilience analysis. The work will be
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employment is governed by the Fixed Term Research Contracts Act (Wissenschaftszeitvertragsgesetz – WissZeitVG). Supervisory team : Supervisor: Prof. Dr. Martin Tajmar Co-supervisor
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, Data Science, Machine Learning, or a related field. Experience and skills · Strong knowledge of AI, Machine Learning, data-science (e.g., neural networks, deep learning, autoencoders, GANs, active
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perform specialized fabrication and experimental tasks and develop a deep understanding of the theoretical framework and modeling tools. This will require communication skills, capacity to learn, and
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of computer vision and machine learning Proficiency in English (oral and written) Experience with Deep Learning is a plus To Apply: Please send a long CV, motivation letter, and academic transcripts to Prof
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heating and cooling, storage, and local electricity grids. A key goal is to translate methodological innovations in deep learning into practical tools for sustainable urban energy systems, supporting