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). The project focuses on developing computational models for cancer risk assessment, integrating multiple types of data and risk factors. The main objective is to design and apply machine learning and deep
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in radiotherapy with the goal of enabling fully adaptive radiotherapy. The work is based on deep learning, where models are trained on generated or clinical data. The project is carried out in
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to allergen-specific immunotherapy. The research group conducts experimental and translational research in close collaboration with specialists at Skåne University Hospital. The team collects samples
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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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Research, SSF. Project description You will work in the RESIST project and primarily contribute to the area of protection of distributed AI. RESIST is in collaboration with Linköping University, Örebro
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. The postdoctoral position is based at the Centre for Theology and Religious Studies (CTR) and includes a collaboration with the Humanities Lab at Lund University (HumLab ) and the Digital Archaeology Lab (DARKLab
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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
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periods abroad in a collaborating lab is required You are expected to be somewhat accustomed to teaching, and to demonstrate good potential within research and education. The following experience will
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digital advancements are transforming scientific communication, writing practices, and learning in STEM. The division offers ample opportunities for collaboration and networking, both within Chalmers and
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, and stimulating environment. We value communication and collaboration and a workplace that promotes learning and development for all employees. We are also committed to building a safe and positive