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control system that enhances Annual Energy Production (AEP), reduces mechanical stress, and improves fault detection using machine learning (ML) and physics-based modelling. The candidate will gain hands
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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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an exceptional opportunity to conduct cutting-edge research at the intersection of machine learning, healthcare, and computational modelling, contributing to real-world clinical impact. What is offered
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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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(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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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