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in research and development of sustainable energy conversion technologies. We are recognized as global leaders in this field, supported by state-of-the-art facilities and deep expertise. Our
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Python and Pytorch as well as deployment on GPU clusters. A strong publication record in graph neural networks, geometric deep learning, representation learning, machine learning–based molecular/materials
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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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chatbots and other virtual assistants that can help students learn more effectively or prepare for exams, or support teachers in repetitive tasks. We are looking for a highly motivated and experienced
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robust models – and for clinicians, whose goal is to determine when to trust the models. We therefore seek candidates who have strong technical background in working with large-scale deep learning models