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Field
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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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machine learning for time series, geospatial data or dynamic models; ideally experience with deep learning frameworks (e.g., PyTorch). Strong analytical and conceptual skills for designing and interpreting
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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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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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for machine learning, with research topics ranging from decentralized and federated optimization, adaptive stochastic algorithms, and generalization in deep learning, to robustness, privacy, and security
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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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developing a digital twin, employing machine learning and numerical computations of atomistic processes. At IKZ, a kinetic Monte Carlo tool has been developed in the programming language julia. This allows a
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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
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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