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Field
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. This insight opens the door for enjoying the real world. The candidate further develops efficient and robust algorithms for realistic settings in terms of data and computing resources and collaborates to address
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algorithm development, data analysis and inference, and image analysis Ability to do original and outstanding research in computational biology, and expertise in computational methods, data analysis, software
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their own research programme as well as support in the delivery of AI upskilling and expertise transfer to government. What you would be doing The objectives for the role are: to deliver ground-breaking
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. The employment period will be three years of full time with no teaching obligations, and there is a premise for employment that the PhD Research Fellow is enrolled in USN’s PhD program in technology within three
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collaboration with industry partners. This work will apply optimal control theory, including machine-learning algorithms and Bayesian estimation, to coherent control of nitrogen-vacancy centers in diamond
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(CPS) for aquaculture, to sensors and platforms for maritime applications. The Postdoc’s primary task will be to lead the development of algorithm, software, and hardware to extend the current HAUCS
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The fellow will be responsible for: Building collaborations with our multidisciplinary team (medical physicists, engineers, computer scientists, nuclear medicine physicians) to develop and implement innovative
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scientists, nuclear medicine physicians) to develop and implement innovative AI algorithms applied to medical images To lead effort on enabling translational and physician-in-the-loop AI solutions for medical
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algorithms that integrate general and domain-specific knowledge with data, laying the foundations of next generation machine learning. This will be done by combining the mathematical and computational cultures
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models using frameworks such as PyTorch and TensorFlow. Research experience in medical image analysis using deep learning algorithms. Strong track record in machine learning, computer vision, and medical