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Field
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Computer Science, Biomedical Engineering, Pathology Informatics, or a related field, with emphasis on computer vision and machine learning (summer and fall graduates are also welcome to apply) Proficiency in
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Strong analytical skills and experience in developing and implementing machine learning/AI solutions using relevant languages and frameworks Excellent communication skills and proven ability to collaborate
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will primarily support the Head of School (Professor George Panoutsos, Chair in Computational Intelligence) and his research activities in the area of Machine Learning (ML) for Engineering, focusing
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Learning/Computer Vision. The experience in diffusion models is a plus. Have a PhD degree in computer science/engineering or related disciplines. Knowledge of autonomous vehicles or cyber security will be
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: Genomics, precision medicine, bioengineering, and health data science AI and Digital: Machine learning, robotics, digital health, and cybersecurity Defence and Advanced Manufacturing: Secure systems
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the role Overview of the role We are seeking a highly motivated Research Fellow in Machine Learning to join the PharosAI team, focusing on developing novel machine learning methods in computer vision
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the very people who bring those lessons to our students. Every bit of knowledge, and every advancement, provides our students with an unprecedented, collaborative learning environment, and helps improve
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the role Overview of the role We are seeking a highly motivated Research Fellow in Machine Learning to join the PharosAI team, focusing on developing novel machine learning methods in computer vision
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collaboration between industry, government, and academia. The Australian Institute for Machine Learning (AIML) at the University of Adelaide is the largest computer vision and machine learning research group in
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Janeen Eligibility Requirements Degree: Doctoral Degree. Discipline(s): Business (11 ) Chemistry and Materials Sciences (12 ) Communications and Graphics Design (6 ) Computer, Information, and Data