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Field
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fully funded PhD research studentship in Physics-Informed Machine Learning for Cardiovascular Medicine. This opportunity is open to UK (Home) candidates only. Project Overview Arrhythmias are disorders
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engineering, and hyperparameter tuning to produce resilient and high-performing models. · PhD in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field Strong track record
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, and space hardware. This PhD research aims to develop a comprehensive Mode Selection Framework for Reduced Order Modelling (ROM) in Structural Dynamics—using machine learning to build robust
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machine learning methods to investigate how ecosystem water stress and drought disturbances affect relevant forest ecosystem functioning at various scales. It will enable advanced assessment of forest
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-molecule techniques. Coding skills for data analysis, pattern recognition, machine learning, kinetic modeling, etc. Advanced optics, biochemical wetlab, and/or bioengineering experience. Required: MSc degree
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implementing signal processing algorithms specifically tailored to analyze signals that contain interfering impulsive content, often encountered in data coming from main and pitch bearings. Machine learning
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27 Aug 2025 Job Information Organisation/Company ETH Zürich Research Field Engineering » Other Mathematics » Applied mathematics Mathematics » Computational mathematics Mathematics » Mathematical
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the first call lasts from the 1st of July to 31st of August 2025. Description of specific PhD projects: Machine Learning Interatomic Potentials for Chemical Reactions Hosting: Tallinn University of Technology
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multimodal machine learning. Admission requirements The general admission requirements for doctoral studies are a second- cycle level degree, or completed course requirements of at least 240 ECTS credits
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-learning energy trading algorithms that are able to cope with these challenges. By leveraging real-time data, developed algorithms continuously adapt to market dynamics and respond to changing market signals