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trigger reconstruction architectures for future particle collider experiments, based on deep learning models distributed across multiple hardware processing stages. The mission of this position, based
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ferroelectrics, plasmonics, semiconductors—into photonic and THz architectures. This is an outstanding opportunity for candidates with a strong background in nanofabrication to contribute to cutting-edge quantum
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industrial partner, you will design and implement innovative architectures for real-time detection and control of laser processes. This interdisciplinary role combines artificial intelligence and machine
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. Develop and maintain features in the DataSpaces codebase (C/C++) Customize and optimize Docker-based builds for various CPU architectures (e.g., with and without AVX) Handle dependency management (Mercury
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this 3-year research position in our 3D Geoinformation research group, section Urban Data Science, Department of Urbanism, Faculty of Architecture and the Built Environment. You are expected to contribute
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-glioma synapses. Experimental methodologies include single-cell sequencing (scRNA-seq and scATAC-seq), techniques for mapping 3D genome architecture (HiChIP, Hi-C, Capture-C), and bioinformatics analyses
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 11 hours ago
orbital dynamics using analytic and numerical methods, (2) planet formation theory, (3) exoplanet architectures and demographics using statistical methods, and (4) planetary interior/atmosphere modeling
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learning. However, conventional neural networks are not well-suited to the computational constraints of FHE. The project aims to develop more efficient neural network architectures tailored for encrypted
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, x-ray generator and detector. -Experience with GEANT4 or similar Monte Carlo modeling toolkit. Experience with implementing computational neural network (CNN) architecture. Experience in image
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experimental approach to systematically infer protein-semiconductor hierarchies materials and design de novo hierarchical architectures with atomic precision. The postdoctoral project aims to design de novo