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About us: The applicant will join the Wellcome-funded Imaging Machine learning And Genetics in Neurodevelopment (IMAGINE) lab, in the Research Department of Biomedical Computing. The post will
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-funded Imaging Machine learning And Genetics in Neurodevelopment (IMAGINE) lab, in the Research Department of Biomedical Computing. The post will benefit from the extensive and broad expertise in AI and
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multiple departments within the University of Cambridge as well as the collaborating organisations (RSBP, NIAB and UKCEH). The role holder will investigate machine-learning approaches that advance the core
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considered for Research Assistant. Strong programming expertise in Python and C++, with experience developing real-time robotic and AI systems. Experience in deep learning and computer vision, including
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statistical modelling of high-dimensional data, e.g. penalised model selection and machine learning. Demonstrable understanding of RNAseq and gene expression analysis. Experience/skills handling and securely
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sciences, AI, machine learning or related fields. Strong background and track record in the development of geospatial foundation models from multi-modal Earth Observations is essential as well as strong
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., statistical modelling, Artificial Intelligence/Machine Learning) Experience in computational biology and bioinformatic analysis Proven ability to write detailed, technically accurate reports on complex research
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Networks. Knowledge of and experience in Python, TensorFlow, Keras, or other Machine Learning toolboxes, is essential. Knowledge of and experience in Large Language Models is highly relevant. The successful
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in C++ and/or Python is expected, and experience in model analysis and parameter optimisation is beneficial. Experience in machine learning and neural networks is desirable. The successful applicant
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projects of the MQS group. Our recent research has focused on the theory and applications of variational quantum algorithms and quantum machine learning. We also have activity in quantum optics, so