192 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" positions in Sweden
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% Department Department of Computing Science Show description The Department of Computing Science at Umeå University is looking for a doctoral student in machine learning for software security. The position is
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technology, driven by high-quality research and education, openness and collaboration. As a Teaching Fellow, you will contribute to this goal through engaging teaching and learning in a collegial and inclusive
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covers areas such as pure mathematics, applied mathematics, mathematical statistics, as well as computer vision and machine learning. The department has approximately 150 employees, including 21 full
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modeling, machine learning, and AI techniques applied to biomedical data is a plus. Clinical Proteomics: Experience with clinical trial data, real-world evidence (RWE), and biomarker-driven trial designs is
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dimensions andanalyse particle trajectories using a combination of established tracking algorithms and machine-learning-based approaches. You will further correlate the diffusive behaviour of viruses
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combining two of Europe's new satellite sensors. If you have interests in physics, climate and machine learning, this is the Doctoral student position for you! About us Our team is part of the Division
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evolution across different genomic regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods and statistical analysis (https://cgrlab.github.io
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measurements with fluorescence microscopy. It is considered a merit if you have experience in AI-based or machine-learning-based cell and image analysis. It is considered a merit if you have advanced knowledge
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deployments or data collection in real-world environments) Familiarity with current AI technologies (e.g., machine learning, large language models) and an interest in their application to embodied systems. What
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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