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, quantitative imaging, machine learning, and AI applications in radiology. The research area includes innovative work on developing Deep Learning Based Image reconstruction in CT on Photon Counting Detector
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perception built with machine learning. They will build on the lab's expertise in deep computational models of the auditory system and in particular on recent work building models of prosthetically
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perception built with machine learning. They will build on the lab’s expertise in deep computational models of the auditory system and in particular on recent work building models of prosthetically enabled
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to University and unit-level policies and procedures and safeguards University assets. Develop various machine learning and data mining models including deep convolutional neural networks (CNNs
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experience in Python programming including experience with the Pytorch library and running deep learning models. We are looking for organized, enthusiastic applicants who work well in a team and can quickly
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used by a PhD student, likely starting October 2027, to initiate development of a deep-learning architecture. The refined batch of synthetic data will be used by the PhD student to finalise the deep
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analysis, deep learning methodology development, and clinical translation. The candidate will work closely with multidisciplinary collaborators, including clinicians, imaging scientists, and engineers
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. Demonstrated research experience in one or more of the following areas: LLMs; generative AI; agentic AI or AI agent development; foundation models; multimodal learning; NLP; deep learning; self-supervised
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Complex Data Analysis ○ Areas of Research: Algebraic methods in data analysis, optimization, topological data analysis, geometric deep learning. ○ Considered a plus: experience in programming or course
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research • Deep learning and predictive modeling • Natural language processing and large language models for biomedical data • Drug response prediction and treatment optimization • Biomedical