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About the Role We are seeking a Postdoctoral Research Associate in Machine Learning for Cardiovascular Digital Twins to join a team working on the Precision Health, Cardiovascular Devices and Trials
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-year Postdoctoral Research Associate (PDRA) for the Leverhulme Trust-funded project "Literacy in the Digital Age," led by Dr Yaling Hsiao. Investigating how children aged 11–14 learn across print and
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learning and physics, addressing key challenges in modern quantitative biology. The successful candidate will be responsible for: • Develop and train deep learning models (CNNs, ...) data to predict IPLSs
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Equation, Stochastic simulation algorithms, and approximation methods. ● Experience with single-cell or spatial transcriptomic data analysis. ● Familiarity with machine learning and deep learning
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, extract, and standardise functional information 2. Develop computational tools that integrate evolutionary and functional information using comparative genomics and deep learning approaches 3. Apply
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and deep learning methods for large-scale genomic, clinical, and imaging biobank data, with stable multi-year NIH support. The Zhi Laboratory has a sustained track record of methods development
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design, train and implement ARCA: an AI foundation model for crop microbiomes. You will work at the interface of deep learning, bioinformatics and microbial ecology, using large-scale microbiome and genome
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. Experience with quantitative image analysis and deep learning tools for segmentation and classification (e.g., Cellpose, napari, scikit-image, PyTorch). Experience with 3D culture systems, organoids
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a postdoctoral associate to study the pathophysiology of Parkinson’s disease (PD), in a progressive, preclinical, MPTP rhesus macaque model of disease progression. In particular, we are looking
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, you will design, train and implement ARCA: an AI foundation model for crop microbiomes. You will work at the interface of deep learning, bioinformatics and microbial ecology, using large-scale