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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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. Our lab studies how co-translational processes regulate gene expression and is newly focused on leveraging these insights to create novel molecular tools. One long-term goal of our research program is
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geophysical models developed in parallel projects The work will focus on establishing the geometry, kinematics and reactivation history of basement-rooted structures and evaluating their role in
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, surrogate modeling of scientific processes, workflow automation and adaptive simulation pipelines, and performance analysis and optimization. The candidate will also contribute to and help originate research
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components, integration into a wearable format, and establishing a consistent build, test, and quality-check process so that multiple units can be manufactured with comparable performance. In parallel
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-scale deformation and microstructural analysis - Targeted petrochronological studies on magmatic and deformation events - Integration with regional geophysical models developed in parallel projects
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will play a key role in building a parallelized, agent-driven exploration system and integrating a multimodal detection pipeline, ensuring real-time performance, scalability, and deployment readiness in
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advanced genome-editing tools. In parallel, we develop in-house sequencing technologies to dissect epigenetic and epitranscriptomic modifications at the molecular level, along with high-throughput platforms
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dedicated to improving quality of life across the world. This position will play a crucial role in ensuring the continuous operation and enhancement of our High-Performance Computing infrastructure
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substrates, given their wide commercial availability and application. This process will be carried out through ion exchange and thermal annealing, enabling the formation of luminescent metal clusters. In