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quantitative or computational approaches are required. Prior experience with image analysis, machine learning, signal processing, or structural biology is meritorious but not mandatory. Excellent written and
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Modelling, Applied Statistics, Linguistics, Data Analysis, Large Language Models, Machine Learning. Start date: 1st October 2026 Deadline: 30th April Duration: 36 months Funding: Funded Funding towards
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laboratory. Where to apply Website https://networks.imdea.org/job/phd-position-in-ai-enhanced-secure-6g-services/ Requirements Research FieldEngineering » Communication engineeringEducation LevelMaster Degree
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of the Quantum & Computer Engineering (QCE) department is looking for a highly motivated PhD candidate who is eager to work on AI based solutions for predictive inteligence for MRI scanning. The candidate will
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) approaches. Design predictive maintenance algorithms using machine learning, statistical learning, and digital twin-based models to anticipate failures and optimise maintenance interventions. Integrate AI
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. Experience with machine learning is highly preferred. Ability to work independently and as part of a team. Key Requirements for PhD: Hold a Bachelor's degree with outstanding performance in Physics or related
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Grade Level 13 Salary Range $71,323-131,685/year Type of Position Staff Position Time Status Full-Time Required Education MS Click here for more information about equivalencies: https://hr.uky.edu
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machine learning. The work will be part of a Horizon pilot project aimed at realizing a scenario-based platform for the interactive and comprehensive evaluation of design solutions and mitigation strategies
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. The position requires experience with at least one of the following: Data Science, Machine Learning, Computational Social Science, Big Data. Relevant skills could include statistical analysis, data management
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models