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multiphase flow behavior. The project also involves applying machine learning and computer vision techniques to enhance data analysis, pattern recognition, modeling, and prediction. The role requires a solid
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novel machine learning method development. However, you will be part of a larger cross-disciplinary research initiative involving both computer and material scientists, providing excellent opportunities
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: Help develop a non-invasive computer vision method to track and analyze how hens move in 3D space. You will gain hands-on experience in behavioural studies, animal welfare science, and innovative data
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or more (with none of the sections scoring less than 5.0) • TOEFL score of 550 or more (computer based test 213, internet based 79) • Cambridge/Oxford - Advanced or Proficiency level. Selection
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English IELTS score (Academic) of 6.0 or more (with none of the sections scoring less than 5.0) TOEFL score of 550 or more (computer based test 213, internet based 79) Cambridge/Oxford - Advanced
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or more (computer based test 213, internet based 79) Cambridge/Oxford - Advanced or Proficiency level Selection The selection among the eligible candidates will be based on their capacity to benefit from
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none of the sections scoring less than 5.0) TOEFL score of 550 or more (computer based test 213, internet based 79) Cambridge/Oxford - Advanced or Proficiency level Selection The selection among
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of 550 or more (computer based test 213, internet based 79) Cambridge/Oxford - Advanced or Proficiency level Selection The selection among the eligible candidates will be based on their capacity to benefit
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or more (computer based test 213, internet based 79) Cambridge/Oxford - Advanced or Proficiency level Selection The selection among the eligible candidates will be based on their capacity to benefit from
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to assimilate knowledge at the research level. Understanding and experience in machine learning and computer vision. Knowledge, experience, and strong interest and in AI and XR development. Knowledge and