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countries (HIC). The airm of this PhD project is to understand how E. coli colonization contributes tot he risk of diarrheal disease and infections with AMR and use this knowledge to design interventions
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of mill and production operations. The scientific challenge will be to use the model and machine learning alongside live mill data (temperature, rolling loads etc) to reverse engineer the current
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check the minimum entry requirements for the PhD . Applicants must also satisfy Monash’s English Language Proficiency requirements; Demonstrate knowledge of machine learning, medical image analysis
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with one of the following doctoral research projects. 1. AI-Aided Site Reconnaissance and Rapid Assessments for Settlement Upgrading How can spatial analytics, remote sensing, and machine learning models
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benchmark chemometric and physics-informed machine learning models to monitor, forecast, and ultimately control critical process parameters, implanting these models in advanced control frameworks to optimize
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flow theory or machine learning frameworks (e.g., PyTorch, TensorFlow). Strong written and oral communication skills in English. Personal characteristics To complete a doctoral degree (PhD), it is
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backgrounds such as AI, computer vision, computer graphics, machine learning, robotics, wearable technologies, textile engineering, fashion technology, digital fashion, or related areas are encouraged to apply
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on futuristic technologies in the field of machine learning and computer vision. Hence, we investigate and develop an innovative computation-in-memory (CIM) solution for artificial intelligence accelerator design
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
for the position. Preferred selection criteria Experience with machine learning or other relevant AI technologies Scandinavian language skills Previous experience from industry or research in engineer-to-order
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% of your time), including tutorials and supervision of Bachelor’s theses. This is what we ask of you This is an interdisciplinary project that combines machine learning and AI, probabilistic risk