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Master’s degree in Data Science, Artificial Intelligence, Computational Linguistics, Computer Science. Has excellent academic writing and oral skills in English. Has experience with large language models
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science, computer science, applied mathematics or a related field a strong background in machine learning, material modeling, and metals processing, modeling and simulation (This will be a clear advantage
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Leibniz Association. The following position is available at the Institute subject to approval by the funding organization from October 1, 2025, for a fixed term of three years, in the program area "Next
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(Kingdom of the) [map ] Subject Area: Advanced Nearest Neighbour Models for Active Matter Appl Deadline: 2025/09/10 11:59PM (posted 2025/07/14, listed until 2025/09/10) Position Description: Apply Position
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for downstream tasks. In this project, you will develop novel unsupervised machine learning methods to analyse cardiovascular images, primarily focusing on MRI. In your research you will train models to learn a
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candidate with a strong background in computational fluid dynamics (CFD) and specialized expertise in hemodynamics associated with coronary artery disease (CAD). The ideal candidate will hold a PhD in
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in the SPG. We will make use of models of different complexity up to complex Earth System models, and modelling efforts for different past periods. A personalised training programme will be set up
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cybersecurity allowing thus to validate and receive feedback from on-the-field cybersecurity practitioners. As generative AI (GenAI) platforms and large language models (LLMs) are increasingly integrated
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– from the modeling of material behavior to the development of the material to the finished component. PhD Position in Machine Learning and Computer Simulation Reference code: 50145735_2 – 2025/WD 1
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to remote sensing and simu-lation modeling. A particular focus of our work is on mountain forest ecosystems. A quantitative understanding of ecosystem dynamics provides the foundation for the development