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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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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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– 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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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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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
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models on edge devices Reporting findings and methods in conference and journal papers Your profile Masters, Diploma or equivalent degree in IT/computer science/statistics/applied mathematics/data science
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follow the EngD in Model-Based Systems Engineering Programme. They will be based at a Leonardo site in the UK. Entry requirements: A minimum of an upper-class honours degree (2:1) or overseas equivalent in
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specimens. Key Duties & Responsibilities Generation of Experimental Research Data using Mouse Model and Human Samples. Analysis of High-Dimensional Computational Data. Manuscript and Grant Writing