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education to enable regions to expand quickly and sustainably. In fact, the future is made here. Umeå University is offering a PhD position in Computing Science with a focus on machine learning for graph
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science data. For this position, we're seeking candidates with a background and expertise in Large Language Models, Computer Vision Models, Deep Neural Networks, and/or other 'AI' or Machine learning fields
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intelligence, machine learning, big data and network analysis, computational and Bayesian methods, are encouraged to apply. Minimum Qualifications PhD in Statistics or closely related fields with documented
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managing large multimodal datasets, as well as contributing to analytical studies related to machine learning, clinical decision rules, and time-to-intervention evaluations. Responsibilities include curating
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application development. Deep Learning techniques, Data Engineering, and Semantic Technologies Open-source artificial intelligence, machine learning, statistical estimation methods, software tools, and big-data
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part of a team, able to learn quickly, meet deadlines and demonstrate problem solving skills. Thorough knowledge of web, application and data security concepts and methods. Preferred Qualifications PhD
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to capture the spatial complexity of tumor organization and its relationship to treatment response. This PhD project aims to develop robust multimodal predictive models of platinum resistance using a large
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expertise is required in categorical data analysis, longitudinal data analysis, and risk modeling using statistical and machine learning approaches. Experience with supervising and managing clinical research
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quality monitoring, and/or nature-based water treatment designs. In addition, the candidate should have some experience in AI, machine learning, and/or managing large data sets related to water resources
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conducting research "in the wild" (e.g., field deployments or data collection in real-world environments) Familiarity with current AI technologies (e.g., machine learning, large language models) and an