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explore, and how different ways of structuring learning environments influence curiosity and learning. Computational models will be used to characterise individual differences in information-seeking
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implications for both fundamental and medical sciences. Job requirements MSc degree (or nearing completion) in physics, biophysics, computational biology, or a related field. Strong programming skills (Python
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: Completed, or soon-to-be completed MSc in the biological sciences or different fields in the natural sciences (e.g. computational, mathematical, earth or marine sciences) with a strong interest in ecology and
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. In addition, the following are requirements for the role: Strong programming and quantitative skills, particularly in Python and/or R. Experience in deep learning, machine learning, or large-scale
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deviation from the healthy distribution. But in the absence of labels, how should we direct the model to learn relevant features, and how can we determine which features are relevant? These questions
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technologies in NLP, LLMs, and RAG. Programming skills in Python, including experience with machine learning libraries (e.g., PyTorch, Scikit-learn, Hugging Face Transformers) and development tools (e.g., Co
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technologies in NLP, LLMs, and RAG. Programming skills in Python, including experience with machine learning libraries (e.g., PyTorch, Scikit-learn, Hugging Face Transformers) and development tools (e.g., Co
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technologies in NLP, LLMs, and RAG. Programming skills in Python, including experience with machine learning libraries (e.g., PyTorch, Scikit-learn, Hugging Face Transformers) and development tools (e.g., Co
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of freedom makes it possible to increase the maximum information transfer rate, for instance through mode-division multiplexing: different modes carrying different angular momentum propagate independently
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interactions and microbiome research; an interest in quantitative biology, phenotyping and data analysis; the ability to organise research activities effectively, to communicate research findings to different