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for a research associate position on the topic of deep learning for particle physics.The Cluster of Excellence “Quantum Universe” performs research to understand mass and gravity at the interface between
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. We are working
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. Successful and rapid development and deployment of the technology will ensure EU's leadership in the exploration and exploitation of deep space, the next commercial space frontier. The program is designed
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technology and/or computer graphics as well as interest in fundamental research and experimental working. Strong skills in VR, psychophysics, deep learning or computer simulation are another advantage Job
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deployment of the technology will ensure EU's leadership in the exploration and exploitation of deep space, the next commercial space frontier. The program is designed to achieve the following training
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development and deployment of the technology will ensure EU's leadership in the exploration and exploitation of deep space, the next commercial space frontier. The program is designed to achieve the following
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and data analytics (including machine learning and deep learning); from high-performance computing to high-performance analytics; from data integration to data-related topics such as uncertainty
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distribution of subsurface heterogeneity to illuminate the imprint of past and present deformation. Project 2: Generation and analysis of a high-quality seismic catalogue in Greece and Albania with Deep Learning
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | 3 months ago
description:PhD position in "DynaDeep – Biogeochemical processes in the Dynamic Deep subsurface of High-Energy Beaches" (m/f/d) Background The DFG Research Unit DynaDeep aims to achieve a deeper understanding of
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coherence, optical), including cross-modal fusion and modality distillation • Design a causation analysis framework combining deep learning with causal discovery & inference to quantify the influence