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in machine learning or deep learning for medical image analysis Strong programming skills in Python, with additional experience in C/C++ or other object oriented languages Experience with PyTorch
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be the state estimation of the robotic system from external cameras. Familiarity with existing methods from these domains, such as Deep Learning, Quality-Diversity algorithms, reinforcement learning
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networks. The research will employ mathematical modelling and computer simulation to identify synaptic plasticity rules which enable effective learning in large and deep networks and is consistent with
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related discipline. The candidates will have expertise in computational imaging, with: (i) an algorithmic focus, with particular interest in methods at the interface of deep learning and optimisation
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-dose IL-2 affects the neuro-inflammatory process. You'll use advanced cellular immunology techniques to conduct deep phenotypic and functional characterisation of regulatory T cells (Tregs), establishing
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expertise in analysing/ training models on biological or chemical datasets Proficiency in Python for data science and machine learning Possess sufficient breadth or depth of specialist knowledge with deep
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. You'll use advanced cellular immunology techniques to conduct deep phenotypic and functional characterisation of regulatory T cells (Tregs), establishing their relationship with treatment responses and
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state-of-the-art machine learning and deep learning techniques (such as generative adversarial networks), with empirical fieldwork in Norwegian glacier environments. As a Postdoctoral researcher, you will
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). About the role The project's primary goal is to investigate how low-dose IL-2 affects the neuro-inflammatory process. You'll use advanced cellular immunology techniques to conduct deep phenotypic and
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project will likely use a combination of single particle cryoEM, cryoET, and X-ray crystallography, you should be an expert in at least one of those techniques and keen to learn the others. You also should