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Are you interested in developing mathematically grounded methods for uncertainty quantification in deep learning, particularly for large language models in healthcare applications? Are you looking
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transcription of the provirus, using novel methods to characterize viral genomes, their integration sites and transcriptional activity. The research environment is collaborative and translational, combining
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duration of the education, which corresponds to four years. Position description As a doctoral student, you will conduct research focusing on the development and application of AI-based methods for energy
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motion in non-classical geometries using combinatorial, algebraic, and group-theoretic methods, inspired by the mathematical theory of articulated systems and constraint geometry. Possible tools include
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of methods, the project examines how team resources, audit processes, and organizational contexts shape the quality and credibility of sustainability assurance. The aim of the project is to develop
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department of Energy and Technology, SLU https://www.slu.se/en/departments/energy-technology/ Read more about staff benefits and life as an SLU employee on https://www.slu.se/om-slu/jobba-pa-slu/ Read more
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exclusion. The work duties also include some data analysis and compiling a methods guide. The data gathering requires local travel, while other tasks are completed on site at Lund University. Qualifications
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in quantitative and qualitative analytical methods and, where relevant, AI-based methods carry out data collection, which may include qualitative interviews with patients or healthcare professionals
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framework agreements and wishes to decline direct contacts from staffing- and recruitment companies as well as vendors of job advertisements. Where to apply Website https://web103.reachmee.com/ext/I011/853
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researchers have extensive experience in doctoral education and supervision. More information about the department of Energy and Technology, SLU https://www.slu.se/en/departments/energy-technology/ Read more