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the case of challenging environmental conditions, the method of multi-scale parallel single-pixel imaging has the potential to enable breakthrough advances. The “image processing and AI” group contributes
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systems based on massively parallel hardware architectures Combination of programmable logic, tensor processors and general-purpose CPUs for real-time adaption and scheduling services (e.g., AMD Versal
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GPU-capable, parallelized simulation frameworks. Work closely with experts in HPC and power systems to enhance scalability and computational performance. Disseminate your findings through scientific
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-insurance subsidy of €100 per month Supplementary €550 mini-job allowance to support parallel part-time employment (optional) Application Details Expected start date: March, 2026 AI for Semantic Structurese
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of memory, senescent, and exhausted T-cells with age. The PhD candidates will work on: - Identifying key metabolic pathways involved in T-cell aging using advanced genetic models that allow for parallel
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imaging over multiple generations. In parallel we will build upon our new experimental and computational framework that links phenotype to function at the single-cell level (named “Look-Seq2”). Strong
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strong background in applied mathematics Excellent programming skills (Python, C/C++) Good experience in machine learning and parallel computing Good organisational skills and ability to work both
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implementation of the necessary measurements Cooperation with HTW Berlin and sampling there on site in parallel with the practical odor tests Conducting emission measurements in emission test chambers, HTW Berlin
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engineering Very strong mathematical and algorithmic background Programming experience (Python, C++, etc.) Familiarity with parallel programming frameworks (e.g. MPI, CUDA) Fluent in written and spoken English
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Kunsthistorisches Institut in Florenz - Max Planck Institute, Florence, Italy | Germany | 3 months ago
Islands. Archipelago investigates the network formed by the islands, both large and small, across the Mediterranean. The project considers in parallel the internal complexity of the large islands, each