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Field
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, normalizing flows, VAEs, generative transformers, or related methods. Strong programming skills and experience with modern deep learning frameworks. Experience with large-scale model training, distributed
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/deep learning-based medical image analysis methods for computerised tomography scans (CT scans). Key applications of such ML/DL methods are illustrated by our prior research (PMIDs 33913675, 33234786
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Position Information General Information Position Number POST40 Working Title Postdoctoral Research Associate (Hokmabadi) Division Academic Affairs Department College of Engineering (Col) Work Unit
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, clinical trials, machine learning, optimization, or related methodological areas. Learning and applying deep learning, agentic AI, and other AI methods in assisting research is encouraged. Research
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strong technical expertise in deep learning, such as models for image segmentation, classification, multi-modal processing, foundation models, or agentic frameworks. An extensive background in computer
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strategies. Duties and Responsibilities Design, implement, and evaluate deep learning models for spatiotemporal data, with an emphasis on medium-scale foundation models. Leverage model embeddings in causal
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staff position within a Research Infrastructure? No Offer Description Activities: The scholarship recipient will be responsible for implementing and comparing quaternion-valued deep neural networks
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geomicrobiology are all desirable but not required. The candidate must have a deep interest in phage biology and microbial community interactions with their geochemical environment. The Postdoctoral Associate will
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About the Role This is a full-time Postdoctoral Research Associate post for 2 years, funded through a Medical Research Council (MRC) grant. The postholder will lead or support an imaging-genomics
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Research Associate to develop, scale, and apply artificial intelligence (AI) and deep learning (DL) models for power grid systems. The successful candidate will contribute to scalable AI workflows for grid