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geometry, fluid mechanics, scientific visualization, HPC and distributed computing. Substantial experience in programming (i.e., fluent in two or more common computer languages). Demonstrated experience in
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investigations of charge state distributions, fragmentation behavior under collisional- and electron-based dissociation, and differentiation of peptide isoforms and PTMs using negative ion mode workflows. Research
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individual for a Team Lead Position “Data Curation Unit” in Helmholtz Imaging Reference number: 2026-0035 As part of a distributed cross-center structure, the DKFZ lead will co-develop and implement a unified
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postdoctoral researcher to join the Distributed and Intelligent Connectivity (DISCO) research group, working at the interface between 5G/6G networking and healthcare. The selected candidate will contribute
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. Describe a deep learning project you have executed. Projects in computer vision for microscopy image analysis are especially relevant. Include a link to a code repository if possible. If you contributed to a
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students, distributed at two geographical locations in Aarhus and Roskilde. The Section for Biodiversity is situated in Aarhus and employs about 25 staff members. For more information on the Department see
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. Describe a deep learning project you have executed, ideally a creative use of supervised fine tuning of a pre-trained vision transformer, U-Net architecture, or related topic. Projects in computer vision for
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within own area (e.g., execution, validation, and reporting of medical lab results; storage, distribution/shipping of specimens and material; tissue governance). Collaborate with healthcare professionals
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postdoctoral researcher to join the Distributed and Intelligent Connectivity (DISCO) research group and contribute to applied research at the interface between 5G/6G networking, AI and digital twins, with a
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the exact calculation of the square-root and inverse square-root of the source distribution covariance matrix. This approach offers analytical and computational advantages in comparison to existing methods