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references, and knowledge of English. More information about the English language requirements can be found here: https://www.slu.se/en/education/programmes-courses/doctoral-studies/application-admission
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data-driven production planning affect industrial sustainability—from economic, environmental, and social perspectives. Your work assignments: Conduct life cycle cost analyses (LCC) to assess
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mathematical modelling and data science with diverse disciplines, including ecology, plant physiology, and molecular biology. Your research will deepen our understanding of how living systems respond to stress
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departmental duties, up to a maximum of 20% of full-time. Your qualifications We are searching for someone with a Master’s degree in computer science, media technology, computer engineering, human-computer/robot
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into how algorithmic systems influence the circulation of information and disinformation across digital platforms, and how such processes affect perceptions of credibility, truth, and democratic
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to work at the forefront of multidisciplinary science, integrating mathematical modelling and data science with diverse disciplines, including ecology, plant physiology, and molecular biology. Your research
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qualifications Documented experience with data analysis and programming (e.g., Matlab, Python or R). Experience of risk assessment and/or decision analysis Experience of probabilistic methods such as Monte Carlo
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involves collecting clinical data on the effects of childhood cancer treatment, bioinformatically handling sequence data and developing prediction models, as well as conducting Single Cell RNASeq studies and
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to act in accordance with the university’s policies on equal opportunities and data protection. Other Qualifications You must have at least 240 higher education credits (ECTS), of which at least 60 credits
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, Internet of Things, Systems-of-Systems automation, Machine Learning, Deep Learning, Data Science, Electronic systems design, and sensor systems. Cyber-Physical Systems (CPS) focuses on integrated software