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We are seeking to appoint a Senior Postdoctoral Researcher in Statistical Machine Learning and Deep Generative Modelling to apply and develop cutting-edge deep generative probabilistic models
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per annum. This is inclusive of a pensionable Oxford University Weighting of £1,730 per year. We are seeking to appoint a Senior Postdoctoral Researcher in Statistical Machine Learning and Deep
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breakthroughs in deep learning–powered protein design, recognized by the 2024 Nobel Prize in Chemistry, have enabled the creation of proteins with near-atomic accuracy. Models such as RFdiffusion, LigandMPNN, and
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Vacancies Postdoc position on deep learning based medical imaging for medical robot Key takeaways In this role, you will help develop and implement cutting-edge AI solutions for real-time, image
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volcanic arc using state-of-the-art deep learning techniques and modern seismological processing workflows, reporting to Dr Sacha Lapins. This role offers an exciting opportunity to process multi-year
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 11 days ago
-acid complexes. You will join the Delta team at Inria (Université de Lorraine), working closely with Dr. Yasaman Karami, expert in conformational dynamics, allostery, and deep learning for structural
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self-driven, highly motivated, creative with excellent communication skills in written and spoken English and Cantonese. Expertise and knowledge in AI deep learning model development on histology whole
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Post-doctoral Researcher in Multimodal Foundation Models for Brain Cancer & Neuro-degenerative Disea
of Magnetic Resonance Imaging (MRI). Building on the various contrasts mechanisms available in multi-parametric MRI, we aim to establish deep learning models that predict biomarkers of diseases progression and
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implements machine and deep learning programs. Develops algorithms to deconvolve RNA-seq data and compare them to AI-based methods. Performs follow up validation efforts on cell lines. Minimum Qualifications
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supporting better patient outcomes. The successful candidate will lead the development of multi-modal MRI foundation models that integrate imaging data and radiology reports. Using advanced deep learning