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or streaming data. Develop parallelized and GPU-accelerated learning modules, ensuring scalability and performance efficiency. Build and maintain robust data pipelines for high-throughput modeling over
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concerns, particularly due to its slow renewability and the ecological impacts associated with peatland degradation and greenhouse gas emissions. In parallel with broader efforts to identify more sustainable
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open questions relate to the variability of plant-based by-products, the preservation of functional integrity of bioactive compounds, and their behavior under different processing and storage conditions
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contributes to a world where differences between children and young people are understood and accepted, strengths are capitalised on, and mental health difficulties are prevented or addressed early in life. We
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the role of autologous fat and muscle cells in breast reconstruction with autologous tissue transfer. The position involves working in parallel with several different cell types, which requires the ability
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controlled crosses between individuals of different ploidies. Sequencing data are already available and include RNA-seq and DNA-seq data for these lines, as well as a reference genome for S. latifolia
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of dense laser plasmas and intense laser interactions with matter using particle-in-cell (PIC), hydrodynamic, and/or Fokker-Planck open and proprietary simulation packages. Investigate and develop different
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algorithms for parallel/distributed AI/ML Hardware-aware and resource-efficient partitioning for parallel/distributed AI/ML Optimization of process-to-process communication in parallel/distributed AI/ML
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join our research activities focused on the development and long-term durability of SOEC cells, with particular emphasis on operation under technologically relevant conditions. Electrolysis and green
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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