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Field
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management, cache optimization, and vectorization techniques. Strong understanding of algorithms and data structures, especially those suitable for parallel processing and distributed computing. Understanding
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Requirements: The candidate must be able to demonstrate a deep knowledge of supercomputing software development for massively-parallel computer architectures, and expertise in working with large-scale software
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– as well as Quantum Technologies Aotearoa (QTA), a national multi-institutional research programme. The Department also has particular strengths in affiliated areas through multiple active research
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training and inference of GMMs for large, high-dimensional datasets Explore parallelization strategies to leverage modern GPU architectures Benchmark GPU-based implementations against CPU-based approaches
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programming proficiency in Python and C/C++. Expertise in ensemble learning (e.g., Random Forests, Gradient Boosting, bagging/stacking frameworks). Hands-on experience with parallel or GPU-based computing (CUDA
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tested by isothermal titration calorimetry (ITC) or microscale thermophoresis (MST) in collaboration with the lab of Prof. Andy Lovering. In parallel, minibinder/effector pairs will be co-expressed using
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systems projects. We are developing the Apollo application development and computing environment. We have coordinated several EU projects on distributed and parallel systems including the edutain@grid
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turbulence modelling, CFD mesh generation and use of parallel computing Have relevant experience in working with aerosols and droplets Proficient in handling large data sets and the ability to analysis and
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 28 days ago
optimizing and parallelizing workflows to run on compute clusters. This position is ideal for someone who is looking to gain research experience, enhance their technical skills, or is considering graduate
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computational, molecular and biophysical techniques. During the project you will design the methodology for, and perform the directed evolution of H-transfer enzymes using parallel selection methods, measure