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on developing, implementing, and applying tensor-network and related quantum-dynamics methods. Applicants may indicate a preference for one project or ask to be considered for both. The start date is flexible
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there will be many opportunities for the postdoctoral researcher to expand their professional network and skill set. We are therefore seeking a researcher who is comfortable working with multiple collaborators
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Research Engineer or Postdoctoral Researcher (m/f/d) in the field of Engineering Physics or Material
of microstructured optical fibres, in particular novel hollow-core fibres for applications in high-speed communications, quantum technology, sensor technology, etc. Publication of the achieved results in scientific
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particular novel hollow-core fibres for applications in high-speed commu-nications, quantum technology, sensor technology, etc. Publication of the achieved results in scientific journals and at conferences
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 10 hours ago
pavement networks. This position will focus on modeling and optimizing pavement performance under evolving climate and hazard conditions. This position will advance modeling of pavement life-cycle
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research with Professors Mario D. Molina, Minsu Park, and Blaine Robbins. We seek candidates with research interests and expertise in social networks, group or organizational dynamics, and computational
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07.12.2022, Academic staff The institute for communications engineering offers a position for a doctoral or young postdoctoral candidate with the topic “Communication and coding in quantum networks
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Are you passionate about keeping communications networks secure and trustworthy? Are you eager to explore attacks and countermeasures for QKD systems and to help ensure they can deliver the promised
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and subjective listening tests. Your network and team You will be supervised by Assistant Professor Lauri Juvela, who leads the Speech Synthesis research group at Aalto University. The group works on
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manufacturing datasets, including sensor streams, in-process signals, post-process characterization data, simulation outputs, and digital twin data. Develop, integrate, and evaluate AI/ML models for anomaly