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The Robot Learning Lab in the Department of Computing at Imperial College London is seeking a talented Research Assistant (pre-doc) for an ambitious new project on dexterous robot learning. In
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written communication skills. A collaborative mentality towards research and mentoring. Desired skills and techniques include experience in parallel computation and advanced numerical programming, using
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Global Critical Zone Science Chair to develop and conduct a research program to better understand forest nutrition and nutritional stress in Eucalyptus forest stands in Brazil. Research context: Forests
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turbulent combustion applications, as well as parallel scientific computing. Knowledge of deep machine learning (using TensorFlow, PyTorch, etc.) for multi-fidelity modeling, regression tasks, management and
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Position Summary Functional Genomics of circular RNAs in Alzheimer's Disease. The Cruchaga Lab, member of the NeuroGenomics and Informatics Center, is recruiting a motivated, creative, self-driven
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with Python and R programming languages. Experience with functional genomic technologies including massively parallel reporter assays. Biomedical informatics or biomedical research experience. Preferred
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2025, or as soon as possible thereafter. The project explores two parallel technological routes for converting captured carbon dioxide into microbial biomass: One fully biological, and the other a hybrid
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than 30 people, including parallel post-doctoral researchers in four other countries, and led by Prof Ben Baumberg Geiger at King’s. Secondly, it’s located within the Centre for Society and Mental Health
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
: Expertise in rare event simulation, deep learning, and developing computationally efficient approaches for simulation and modeling in complex systems is highly desirable Experience with parallel computing
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McGill University | Winnipeg Sargent Park Daniel McIntyre Inkster SE, Manitoba | Canada | 3 months ago
imaging system based on the random access parallel imaging (RAP) system platform (https://doi.org/10.7554/eLife.56426 ). The RAP platform quickly collects high-contrast images in multi-well plates using