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Field
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, biology, and epidemiology, developing and applying novel statistical methods and deep learning approaches for global health challenges. The group’s research spans disease modelling, genomic analysis
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record. Requirements: WAM > 80 relevant research experience and top publications high self-motivation Required knowledge MLLM, deep learning, computer vision, generative AI, large foundation model, Learn more about minimum entry requirements .
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record. Requirements: WAM > 80 relevant research experience and top publications high self-motivation Required knowledge MLLM, deep learning, computer vision, generative AI, large foundation model, Learn more about minimum entry requirements .
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learning; distributionally robust optimization; 2) Graph Neural Networks, Large Language Models (LLMs), and geometric deep learning; and 3) federated learning and privacy preserving computing. Basic
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topics: Development of deep learning models Mathematical foundations of machine learning Optimal deployment of AI systems The candidate is expected to hold a relevant MSc degree in Computer Science
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, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to
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, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to apply
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high self-motivation Required knowledge MLLM, deep learning, computer vision, generative AI, large foundation model, Learn more about minimum entry requirements .
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high self-motivation Required knowledge MLLM, deep learning, computer vision, generative AI, large foundation model, Learn more about minimum entry requirements .
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development of machine learning techniques that may be used to triage, classify, and otherwise process material of a distressing nature (such as child exploitation material). It will involve the use of deep