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statistical software. Learning Objectives: Learn about the implementation of the application of machine learning methodologies in plant phenotyping and genotyping for the sugarcane molecular biology lab. Learn
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areas. Key Responsibilities: To independently undertake research in computer vision and machine learning. To produce research reports and/or publications as required by the funding body
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optimization of multi-modal LLMs. Investigate and implement methodologies to ensure AI authenticity, accountability, and the integrity of digital content. Develop and refine machine learning and deep learning
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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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staff in exhibit preparation, including object research, selection, mounting, and installation as needed. Fellowship Learning Goals Learn and follow recognized standards and policies for collection
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of how this machine functions. Elucidating the function is key to unlocking why certain mutations can cause disease such as early onset cardiac disease (through the muscle myosin protein) and how small
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who shares our values and who will support the mission of the university through their work. Qualifications: Ph.D. in a relevant field such as Learning Sciences, Human-Computer Interaction, Education
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results. Preferred Qualifications: Experience with generative AI deep learning and active involvement in data science and machine learning projects. Experience in neural network architecture, cloud
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on machine learning or classical force fields. 3. Familiarity with open-source coding practices (GitHub/GitLab). More Information Location: Kent Ridge Campus Organization: College of Design and Engineering
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: Erlangen Programme for AI” This is a 5-year programme supported by the EPSRC and is a collaboration of mathematicians and computer scientists at the University of Southampton, the University of Oxford (lead