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Field
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transfer, thermo-fluid systems simulation and programming, as well as exposure to software platforms and algorithms for Artificial Intelligence, Machine Learning and Data Analytics. You will have experience
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hospitals. PRIMARY DUTIES AND RESPONSIBILITIES: The qualified candidate will focus on developing new algorithms, including agentic artificial intelligence approaches, for the clinical integration
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Center for Devices and Radiological Health (CDRH) | Southern Md Facility, Maryland | United States | 8 days ago
on the development of optical models, image acquisition software, image processing algorithms, and deep learning algorithms using Zemax, Python, Matlab, LabVIEW, CUDA, and other programming environments. Training
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period at the University of Oslo. Place of work is Department of Technology Systems at Kjeller, Lillestrøm. Job description The person hired in the position will work on theoretical algorithms for robust
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. Implement AI-driven diagnostics and battery state estimation algorithms. Collaborate closely with industry stakeholders to co-develop next-generation battery control solutions, supporting commercialisation
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communication skills. Proficiency in developing deep learning models using frameworks such as PyTorch and TensorFlow. Research experience in medical image analysis using deep learning algorithms. Strong track record in
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models, focusing on industrial image analysis Develop advanced deep learning methods for power battery inspection models Design and implement novel algorithms for AI-based CT imaging Lead experimentation
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, Effects, and Criticality Analysis (FMECA), functional FMECA, advanced sensing techniques, sensor and operational data fusion, data analytics, and machine learning algorithms for condition monitoring, fault
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data-driven analysis algorithms for the assessment of thin-film solar cell fabrication processes within NOMAD Oasis installations. The team is responsible for the installation and development of (meta
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of Electrical Engineering or related areas. - In addition, the candidate should demonstrate solid knowledge in electric power systems and in the development of optimization algorithms and intelligent systems