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Helmholtz-Zentrum Berlin für Materialien und Energie | Berlin, Berlin | Germany | about 2 months ago
the Job related to staff position within a Research Infrastructure? No Offer Description Work group: Matter and Accelerator Infrastructures Area of research: Scientific / postdoctoral posts Job
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-edge research, education, innovation, and industrial partnerships, ensuring a real-world impact on society. The unit operates within HiTech, a research incubator and accelerator that promotes a
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. The successful candidate will collaborate closely with Profs. Vinicius Mikuni, Hironao Miyatake, and other members of KMI, to develop data science techniques to accelerate discovery from the vast amounts of data
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: https://agaur.gencat.cat/es/beques-i-ajuts/convocatories-per-temes/Ajuts-postdoctorals-Beatriu-de-Pinos-BP-2025 The overarching goal of the research project developed by the group is to investigate robust
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devices for medical imaging and reaction monitoring, as well as for the development of sustainable photocatalysts. In this role you will develop machine learning (ML)-accelerated quantum mechanics in
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stimulated Raman transitions on free-falling 87Rb atoms. The phase shift of the atomic interferometer is proportional to g, the acceleration due to gravity, which we measure with a sensitivity greater than
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on our values of excellence, innovate, respect, teamwork, and integrity. Supported by Cancer Research UK and additional funding from external grants and industry partnerships, we aim to accelerate
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Cornell University, Cornell Laboratory for Accelerator-based Sciences and Education REU ID: Cornell-CLASSEPhysics-CBBREU2026 [#31314] REU Title: CBB REU 2026 REU Type: Student programs Location
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record of supporting the professional development of staff. Preferred Qualifications: PhD degree in a scientific or engineering discipline relevant to accelerator physics. Extensive prior experience in
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Description Evaluation of the robustness of ML algorithms executed on a non-hardened accelerator through circuit-level fault-injection The project addresses the challenges of deploying AI applications