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Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. | Dortmund, Nordrhein Westfalen | Germany | 3 months ago
fields Experience with image analysis, or computer vision Good knowledge of basic machine learning techniques, such as variational autoencoder Good presentation and writing skills Proactive, independent
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. Project Overview The project focuses on developing and applying advanced CFD models for aeroengine oil systems. There will also be opportunities to integrate machine learning techniques for building lower
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The International Institute of Molecular Mechanisms and Machines Polish Academy of Sciences | Poland | about 2 months ago
3 Aug 2026 Job Information Organisation/Company The International Institute of Molecular Mechanisms and Machines Polish Academy of Sciences Research Field Biological sciences » Biology Researcher
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mathematics, machine learning, photonics, and clinical practices in vision. Be part of a multidisciplinary research team spanning science and engineering, psychology, and healthcare. Access state-of-the-art
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The Max Planck ETH Center for Learning Systems (CLS) addresses cross-disciplinary research questions in the design and analysis of natural and man-made learning systems. The excellent engineering
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Strong Python skills and experience with data manipulation Basic machine learning knowledge (equivalent to at least an introductory course) Additional skills (nice-to-haves) Experience with website
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with at least one year of experience in applying analysis and synthesis methods and research methodologies in computer and communications engineering or computer science. The successful candidates will contribute
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one year of experience in applying analysis and synthesis methods and research methodologies in computer and communications engineering or computer science. The successful candidates will contribute
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embed user-defined conditions and structural constraints directly into machine learning routines to achieve high-resolution 3D interpolation of rock mass properties. These synthesized geotechnical fields
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, machine-learned interatomic potentials, molecular dynamics, kinetic Monte Carlo modelling and comparison with experimental data from the Faraday Institution FAST programme. Faraday Institution PhD students