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Field
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pipelines for high-throughput modeling over heterogeneous or sparse datasets. Conduct system profiling, model benchmarking, and empirical evaluation across different computing architectures. Explore novel
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partitioning for parallel/distributed AI/ML Optimization of process-to-process communication in parallel/distributed AI/ML Enhancement of AI/ML with in-network computing & processing Adaptation & optimization
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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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of infectious diseases. • Experience with data analysis using statistical inference techniques. • Experience with health economic evaluations. • Experience with parallel and/or high-performance computing
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field from an accredited institution. Demonstrated skills in creative problem solving and troubleshooting Experience with parallel computing and multi-core \ multi-threaded programming libraries Knowledge
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28 Jan 2026 Job Information Organisation/Company Universität Siegen Research Field Computer science » Informatics Researcher Profile First Stage Researcher (R1) Application Deadline 11 Feb 2026 - 22
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ecotypes and seek to identify their associated and underlying genetics. Specifically, it will examine parallel evolution of genomic divergence, gene expression levels, and alternative splice variants
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, lineage-tracing, and computational approaches to address clinically relevant questions in cancer and drug development. Our work is carried out in close collaboration with national and international partners
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distortions in the presence of a shallow crustal hydrothermal system at a model caldera volcano. The model will use the phase field approach and be implemented in Alya, the parallel multi-physics Computation
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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