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@umoncton.ca]Context & Motivation:Because of their extreme computational needs where workloads demand rapid and significant shifts in power consumption, next-generation high-performance computing (HPC
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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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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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(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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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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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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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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– 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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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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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