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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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familiarity with machine learning frameworks (e.g., PyTorch) Deep interest in knowledge graphs, LLMs, and open science A passion for tackling complex scientific challenges, a creative mindset for developing
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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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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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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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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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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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programming and know how to use version control. ▪ You are experienced in the usage of machine learning (e.g., Actor-critic algorithms, deep neural networks, support vector machines, unsupervised learning
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, development, and evaluation of Machine Learning and Deep Learning methods Prototype development Literature review Publication and presentation of scientific results in international conferences and related
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the 01.10.2022. Your Responsibilities: You will work at the cutting edge of privacy-preserving deep learning research with a focus on one or more of the following topics: - Optimal model design for differentially