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Pneumatic Tires, Structure-Process-Properties Relationships. How will you contribute? Do you have proven skills in data analysis, machine learning, as well as in mathematical and computational modelling? You
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sustainability, performance, and reliability. Our research leverages optimization techniques, applied machine learning, and statistical analysis to achieve these objectives. Through the DecAI project we will work
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. These workflows will then be applied in relevant Saudi Arabian contexts to help discover new ore deposits. The position will combine techniques from geological modelling, geostatistics, machine learning, and
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) assess future changes in these patterns under different global warming scenarios. Requirements: The successful applicant should hold a MSc or PhD degree in physics, mathematics/statistics, climate science
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this will include: Demonstrated expertise in data analysis and simulation Familiarity with C++; and proficiency in the use of ROOT and Geant4, and interest in machine learning techniques Knowledge
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completion) in AI, Machine Learning, Data Science, Control or Energy Systems Engineering, or a related field. Strong expertise in AI for real-time systems, predictive analytics, or Digital Twins. Experience
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data, MRI data, and other types of data. Contribute to projects at LCBC with data analysis, development, and implementation of advanced machine learning models. Write and publish scientific articles
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applications* in close collaboration with other discipline experts (software, microelectronics and applications engineers). * except for RF payloads. ** including artificial intelligence and machine learning
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fields: AI (machine learning, big database, etc) Semiconductors
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records from satellite data, and/or improved methods of uncertainty characterisation, including the use of artificial intelligence and machine learning to improve or analyse satellite climate data records