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Field
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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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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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Fagan Application Deadline: Applications accepted all year round Details Background: Clostridioides difficile is the leading cause of healthcare-associated infections and is notoriously difficult to treat
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is expected to have strong computer and analytical skills and be comfortable using a variety of hardware platforms and specialized software tools. Duties include: Perform data processing and analyses
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at the earliest on 1st August, 2026. The position is funded by the Marie Skłodowska-Curie Doctoral Network (MSCA-DN), on “Understanding Lipid ImmunoMetabolism to treat disease” (UNLIMITED) within the Horizon Europe
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range transducers and arrays. Additionally, a high-performance computer cluster is available at Bristol can be used to run large and parallel models. You will have full access to these facilities. You
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setup will allow the exploration of global flow structures, large-scale recirculation, and the transition to the fully heterogeneous regime under realistic industrial conditions. In parallel, smaller
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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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mission is directly tied to the humanity, dignity and inherent value of each employee, patient, community member and supporter. Our commitment to learning across our differences and similarities make us