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these plants. The post-doc is expected to build upon existing in-house tools and, where applicable, enhance them by means of AI (machine learning) and data-driven methods. These models are aimed to support
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an increased interest in adapting and developing the latest machine learning methods for the purpose of malware detection, and preliminary results are encouraging. The specific goals of this project include
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Are you interested in developing machine learning algorithms that provably help us make better decisions? Join us as a post-doc in the Division of Data Science and AI, Department of Computer Science
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. The candidate is expected to have an overall interest in AI concepts and methods, in particular human-centred AI, and expertise in formal models and machine learning, as demonstrated by publications and other
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Join and help us to derive global forest biomass data from the European Space Agency’s Biomass satellite mission. If you have interests in remote sensing, machine learning and forests, this is the
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a strong constellation of both traditional applied biostatistics and expertise in artificial intelligence and machine learning, which is undergoing rapid development. The clinical activities
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. The position bridges machine learning and molecular science, with opportunities for collaboration, mentorship, and impactful research. About us The Department of Computer Science and Engineering (CSE
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at: https://www.umu.se/en/department-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data driven models
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multi-modal perception and machine learning. Current noninvasive agricultural monitoring systems rely primarily on passive sensing, which limits sensitivity to early-stage plant stress. This project
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-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data driven models for complex data, including temporal data