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of industrial processes. In a joint effort of both institutes, the Department AI4Quantum – Machine Learning for Quantum Simulation and Computing and Thermal Energy and Process Engineering are looking for a PhD
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project involves interdisciplinary research at the interface of computer science and mathematics, with a focus on bivariate molecular machine learning for modeling molecular interactions and properties
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the development and application of probabilistic inference methods and machine learning techniques for quantitative uncertainty modeling and for the integration of heterogeneous climate data
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Description In this project, we develop machine learning models for prediction of optical properties of chiral molecules based on DFT/CCSD data which we calculate ourselves. We include derivative information by
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action recognition, and enable seamless collaboration between humans and machines. Long-Term Human-Technology Evolution: investigate the longitudinal impact of human-technology interaction on learning
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project involves interdisciplinary research at the interface of computer science and mathematics, with a focus on bivariate molecular machine learning for modeling molecular interactions and properties
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Description For our location in Hamburg we are seeking: Doctoral Researcher in Machine Learning and Data Processing in the Field of Seismic Measurements Remuneration Group 13 | Limited: 3 years
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the development and application of probabilistic inference methods and machine learning techniques for quantitative uncertainty modeling and for the integration of heterogeneous climate data
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microstructures along the entire process chain using machine‑learning (ML) techniques and validate soft‑sensor outputs against laboratory reference measurements Perform systematic laboratory flotation experiments
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, their achievements and productivity to the success of the whole institution. At the Faculty of Mechanical Science and Engineering, Institute of Manufacturing, the Chair of Forming and Machining Technology is offering