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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Gorlitz, Sachsen | Germany | about 1 month ago
programming skills in languages such as Python, C/C++ and CUDA # Familiarity with modern deep learning frameworks like Tensorflow 2.x.x, PyTorch # Mandatory experience with High-Performance Computing (HPC
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sequencing output. This project brings together chemical biology, molecular biology, and computational science to achieve direct, single-molecule resolution of RNA cap structures. Job-ID: V000015123 Field
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Center for Advanced Systems Understanding, Helmholtz Center Dresden-Rossendorf | Germany | about 1 month ago
environment Excellent programming skills in languages such as Python, C/C++ and CUDA Familiarity with modern deep learning frameworks like Tensorflow 2.x.x, PyTorch Mandatory experience with High-Performance
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. For computational analyses, the successful candidate will have access to the high-performance computing infrastructure of the Leibniz Supercomputing Centre (LRZ) and dedicated data management support. We offer close
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English skills High level of motivation for independent and team-oriented research work Proficient computer skills, particularly in MS Office (Excel, Word) Flexibility, commitment, team spirit, and a strong
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, quantitative readouts, define performance metrics, and validate results experimentally, helping convert laboratory scale prototypes into a compact, portable system. Your Profile: The successful applicant must
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | about 1 month ago
Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Area of research: Scientific / postdoctoral posts Starting date: 01.04.2026
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qualifications: • A completed Master’s degree (or equivalent) in a relevant discipline, such as philosophy, neuroscience, psychology, medicine, law, social sciences, computer science, or a related field • Strong
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strategies), funded by the German Research Foundation (DFG). The successful candidate will contribute to evidence synthesis, develop mathematical models of TB treatment, and conduct health-economic analyses
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occurrences along gradients of anthropogenic stress. Additionally, dispersal and connectivity information will be included to enhance SDM performance. Our aim is to integrate abiotic and biotic factors