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-flexible technologies, and integrate machine learning-driven digital twins for predictive combustion modeling. The research program will cover a wide range of e-fuels (H₂, NH₃, CH₃OH, DME, OME) and their
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research sections. We broadly cover digital technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet
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knowledge of wireless communications, and signal processing. You have at least intermediary knowledge of machine learning algorithms, including federated learning, split learning, and graph neural networks
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operational data and machine learning. You will be based at UCL mechanical Engineering, and collaborate with industry and port partners on system design, prototyping, and lab-based trials. Key responsibilities
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bio materials and porous materials PhD student candidate 2 with background in computer science, AI, machine learning or related fields with the experience in CFD, ANSYS, COMSOL The successful candidates
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Engineering Operations Research Appl Deadline: (posted 2025/06/24, listed until 2026/06/23) Position Description: Apply Position Description Overview Susquehanna is expanding the Machine Learning group and
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drug design” is led by Docent Juri Timonen, at the Division of Pharmaceutical Chemistry and Technology. Our aim is to create new machine learning and artificial intelligence methods to accelerate drug
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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