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Field
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for structural biology. This project sits at the intersection of X-ray scattering and deep learning, aimed at integrating experimental data to predict protein ensemble structures. As an Empire AI-funded fellow
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equivalent qualification with one to two years of advanced research experience in generative AI, visual computing and deep learning, and must have no more than five years of post-qualification experience
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modern deep learning frameworks (e.g., PyTorch) and evaluate them with a focus on interpretability, robustness, and real-world applicability in healthcare settings. The role also involves developing
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-level detection capabilities. Their work involves enhancing the existing deep learning models to ensure high detection accuracy and improve navigation within open-field environments. This person will also
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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 CT with work in collaboration
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, machine learning, and deep learning Good written and oral communication skills Experience in leading research projects Proficiency in basics of programming languages such as Python Self-Motivated and takes
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, a novel spatial discovery proteomics concept that integrates microscopic cell phenotyping with deep-learning based image analysis and global MS-based proteomics. This unique method was recently
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particular emphasis on deep-field observations. The position provides access to large, high-impact JWST datasets and opportunities to contribute to multiple ongoing programs, as well as to a broader portfolio
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bioinformatics, deep learning and/or biomedical image and clinical data analysis (e.g. Linux, R programming) is essential. The appointees will need to perform data analysis of single cell RNA-sequencing
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Learning with a focus on in vitro fertilization (IVF) at Faculty of Technology and Society. Work duties Running cutting-edge research in Machine Learning (ML), focusing on Deep learning and on-device Large