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Field
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models Experience in working with subsurface imaging Proficiency in leveraging GPUs and distributed training for large-scale datasets is highly desirable Good background in image analysis/computer vision
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United Kingdom Application Deadline 21 Nov 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
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Received General direction from the assigned supervisor. Supervision Given None. Required Education Doctoral degree in Physics, Astronomy, Electrical Engineering or Computer Science from an accredited
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Responsibilities: Conduct advanced R&D in the theoretical and practical evaluation of quantum key distribution technologies and quantum cryptography implementations. Develop co-simulation pipelines and digital twin
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to policy and practice. CHL envisions a diverse humanitarianism that embraces the agency of affected people and promotes distributed power, social justice, and equity. At Deakin, CHL sits within the Faculty
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Postdoctoral Research Fellow position in statistics, genetics, and biomedical AI. The lab develops cutting-edge theories, methods, and computational tools for integrating large-scale, heterogeneous biomedical
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The National Energy Research Scientific Computing Center (NERSC ) at Berkeley Lab seeks a highly motivated Postdoctoral Researcher — Scientific Machine Learning (NESAP) to join the Workflow
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early-career researcher in developing an independent research program in semiconductor quantum photonics, with the goal of securing an ERC Starting Grant. The vision for our group We are advancing
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Portugal Application Deadline 21 Nov 2025 - 23:59 (Europe/Lisbon) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme
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of distributed optical sensing techniques developed in ECSTATIC, such as novel distributed acoustic sensing (DAS), on trackside telecom fibres, for the condition monitoring of railway infrastructure, focusing