127 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" scholarships in Germany
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simulation environments, numerical methods, or machine learning approaches is an advantage Fluent command of written and spoken English is necessary; German is an advantage but not required High degree
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Freiberg, Sachsen | Germany | about 2 months ago
separation models to control flotation processes. Your tasks # Develop and implement soft‑sensor concepts for continuous monitoring of ore microstructures along the entire process chain using machine‑learning
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of molecular and biological matter using X-ray and neutron scattering. One of the research areas is the development of machine learning (ML) based approaches to efficient analysis of the vast data amounts
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biological matter using X-ray and neutron scattering. The main research areas are materials for photovoltaics, proteins in solutions and at the interfaces, complex nano-structured materials and machine
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posts,PHD Thesis Starting date: 30.10.2025 Job description: DESY Foundation models are multi-dataset and multi-task machine learning methods that once pre-trained can be fine-tuned for a large variety of
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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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approaches are gaining importance for autonomous vehicles. However, the training and certification of autonomous systems with machine learning components is a huge challenge, since the learned behavior is
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Requirements: Applicants should hold an MSc or Diploma in Engineering, Computer Science or a related discipline. Background in Machine Learning and Artificial Intelligence. Strong programming skills (Python
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
properties (hardness, yield and tensile strength) and corrosion profile (rate and localization). This work focuses on machine learning-assisted PSPR optimization of recently developed lean Mg-0.1 Ca alloy
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on machine learning assisted PSPR optimization of recently developed lean Mg-0.1Ca alloy produced by PBF-LB. After identification of the most relevant parameters adopting a design of experiments