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using LLMs in therapeutic settings: data confidentiality, algorithmic biases, and limitations in contextual understanding. Study the acceptance of these tools by both patients and healthcare professionals
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on the development of algorithms for ECG signal analysis and validation of novel biodegradable ECG electrodes. The contract will be within the framework of the “Green Electrodes for Sustainable Electrophysiology
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Engineering, Databases, Computer Networks, Computer Vision and Graphics, Algorithms, and Computational Biology. Salary and Conditions of Service Remuneration package will be driven by market competitiveness
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develops solutions for a range of vision tasks via machine learning and deep learning algorithms. The SSUDIO project aims to identify various objects of interest from shipboard 3D scans by training computer
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algorithms for microscopy image analysis problems (primarily 2D timelapse data), which are driven by real applications in life science research Develop solutions to integrate large foundation models
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National Aeronautics and Space Administration (NASA) | Hampton, Virginia | United States | 2 months ago
questions in Earth System science is also a goal of this opportunity. Efforts are expected to be conducted in collaboration with the SAGE algorithm/data processing and validation teams, as
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in the 2025 QS World University Rankings by Subjects. We are hiring a Research Fellow in Signal Processing and Machine Learning to develop signal processing and machine learning algorithms and methods
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emphasis on questions grounded in data that are generated by human activity, including computational social science (e.g., algorithmic accountability and the interplay of data science with policy, law, and
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contextualized by existing expertise in existing methods and state-of-the-art in the field. The position includes algorithm design, software implementation, and validation on experimental datasets. You will
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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