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datasets Proficiency in Python for data science and machine learning Possess sufficient breadth or depth of specialist knowledge with deep learning architectures including generative models, particularly
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and studying the phenological migration behavior of small insects using the terra-mobile platform on the Salter Research Farm. Analyze data and summarize results by writing scientific papers
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. The department has a strong community on related topics: research groups working on digital health and wellbeing , network science , computational social science , and various topics in machine learning. You will
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available single-cell sequencing data generated from patient samples and mouse models, we will enhance and apply machine-learning based algorithms to deconvolute bulk tumor RNA-seq samples to distinct immune
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(e.g., based on physiological signals or direct inputs from occupants) and developing algorithms, including machine learning methods. The work will include statistical modelling, data-driven modelling
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the risks. You will have: a PhD in one of the relevant STEM disciplines, such as mathematics, statistics, computer sciences, theoretical food, ecological or physical sciences, etc. skills in mathematical
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visual representation and analysis of large-scale 2D/3D scientific data. This position resides in the Data Visualization Group in the Data and AI Systems Section, Computer Science and Mathematics Division
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to science. This is the first large-scale study of its kind, and your results will establish a legacy of scientists working with funding councils to defend their research. Cutting-edge machine learning
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learning, transfer learning, foundation models, and self-supervised learning. Experience in dealing with large medical datasets (e.g., electronic health records data or medical images) Ability to use high
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experiments Experience with machine learning techniques and tools Ability to work in a large international collaboration Hands-on problem-solving skills and clear and concise verbal and written communication