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. AAS Degree in Computer Science: https://www.bellevuecollege.edu/cs/aas CS students at Bellevue College complete mostly Math, Physics, Humanities, and Social Science requirements as part of their first 2
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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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increasingly shapes biomedical research and healthcare decision-making, we also value candidates who can help students critically understand how algorithmic systems affect equity, access, bias, and real-world
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algorithms, computational complexity theory, and information theory Relevant coursework and experience in spiking neural networks, and statistics A strong electronics background, including experience in
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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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to sign the contract. More information is available on: https://www.dges.gov.pt/pt/pagina/reconhecimento . Workplan and the objectives to achieve: This work aims to develop a numerical approach based on
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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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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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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