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testing data Development of machine learning models for battery health assessment and remaining useful life prediction Job Requirements: PhD degree in Electrical Engineering or related subjects. Expert
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, interdisciplinary initiatives, and industry partnerships at national, European, and international levels. Qualifications: PhD in Mechanical, Electrical, Computer, Civil and Environmental Engineering, or a closely
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intersection of machine learning and life sciences, developing next-generation models that improve our understanding of human biology and enable more proactive, personalized healthcare. As an Industrial PhD
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integration, algorithm development and the creation of machine learning tools required for the project’. The successful candidate must have advanced knowledge of computer engineering, particularly of artificial
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Predoctoral Researcher (PhD Candidate) in Computational Simulation and AI for Therapeutic Ultrasound
research. • Availability to work on-site in Madrid (Spain). • Ability to enrol in an official PhD programme in Spain. • Interest in numerical simulation, machine learning and clinical applications of focused
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hemocompatible coating strategies to improve membrane–blood interactions. - Model and optimize membrane performance using computational tools, machine learning, and artificial intelligence Work Plan - Synthesis
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: PhD degree in Electrical Engineering, Computer Science, or related field PhD students who have completed/are completing their thesis are welcome to apply Knowledge and experience in computer vision
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https://phd.fbk.eu/calls/detail/artificial-intelligence-and-machine-learning-fo… Requirements Research FieldOtherEducation LevelMaster Degree or equivalent Additional Information Work Location(s) Number
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control Strong background in machine learning and data-driven modeling for engineering systems Experience with scientific programming (e.g., Python, MATLAB) and numerical methods Proven ability to conduct
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PhD Stipend in machine learning methods for the analysis of IoT time-series data. At the Technical Faculty of IT and Design, Department of Computer Science, one PhD stipend in machine learning