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‑classical algorithms to tackle domain‑specific, computationally demanding problems. Methods will be designed for near‑term (NISQ‑era) deployment, with models evaluated for expressivity, training stability
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will be designed for near‑term (NISQ‑era) deployment, with models evaluated for expressivity, training stability, scalability, and resource requirements on representative problem sizes, and
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watermarked audio data, improving content-based audio watermarking, and evaluating robustness against removal, spoofing, adversarial attacks, and realistic downstream processing. Your role and goals As the
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-on experience in nano- and OLED fabrication, characterization and electronics is required. The applicant should hold (or expect soon) a PhD degree in a suitable field. Good command of English (both verbal and
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Postdoctoral Researcher, you will take primary responsibility for developing deep content-based watermarks for audio and work jointly with a doctoral researcher on robustness, evaluation, and generalization
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and social sciences and interact with city officials and developers Your experience and ambitions PhD in a relevant field (e.g., planning, urban studies, economics) Demonstrated expertise in housing
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sustainability performance. Build mentoring skills by helping and advising PhD researchers. Lead and write peer-reviewed articles for high impact journals. Participate in events, give expert talks, support in
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letter writers. Evaluation of the applications may start immediately. For more information about the role, please contact Prof. Miguel Caro ([email protected] ). For questions related to the application