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be a member of the Faculty of Physics and Astronomy and the Faculty of Mathematics and Computer Science. The appointee is expected to play an important role in further enhancing the research
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! Fraunhofer Institute for Computer Graphics Research IGD www.igd.fraunhofer.de Requisition Number: 80165 Application Deadline: 09/14/2025
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engineering, computer science or a comparable subject You have good experience in Python You have basic knowledge of the theory and methods in machine learning Good language skills in German and/or English What
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applications for a Full Professorship (W3) in “Multimodal Imaging” (f/m/d) to be filled at the earliest possible date. We are searching for a researcher with an internationally visible, original research program
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(at the time of contract) for that position. Job-description: - evaluation of mass spectra from the Cosmic Dust Analyser onboard the Cassini space probe - collaboration with a computer scientist who is
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systems for measurement processes, or innovative hardware and software for quantum computers and quantum sensors: we develop tomorrow's technology in-house for a sustainable and secure society. When will
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Master Thesis - Development of ligand conjugated lipid nanoparticles for targeted T cell delivery...
biological samples' 3D structure and molecular identity. At iBIO, we bring together cutting-edge science from biology, chemistry, engineering, and computer applications. Our overarching aim is to obtain a
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(www.stelloslab.com) is an internationally recognized research group at the forefront of RNA biology and cardiovascular science. We harness integrative computational and experimental strategies to unravel how RNA
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. The Photonic Networks and Systems department is conducting research on the next
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Computer Science, Artificial Intelligence, Materials Science, or a related field Strong programming skills in Python, ideally with experience in image processing and deep learning using PyTorch or similar frameworks