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electronics for space-borne Earth climate observations. With this goal in mind, the PhD project will explore ultra-low-noise detectors and advanced terahertz receiver architectures. Major responsibilities Your
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and/or dynamic approaches to detect them in the code or prevent their execution at runtime. Keywords for this project: code analysis, static analysis, reverse engineering, defense mechanisms
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Technology, Campus Norrköping. Your work assignments This position is motivated by the need for reliable visualization and data analysis methods that support understanding of the increasing amount
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long-term experiments. Your profile The candidate must have a PhD degree in silviculture and/or forest management or a very similar subject. The candidate must have proven experience in data analysis and
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of segregation, culture, and politics, as well as social network analysis and computational text analysis. IAS is also home of the Swedish Excellence Center in Computational Social Science (SweCSS
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in biology, ecology or forestry, with documented specialization in community ecology, bird or bat ecology, and/or restoration ecology. Experience in design, execution and analysis of acoustic data is
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expected to work across the full pipeline, from sensor-based measurements to data analysis, supporting a holistic approach to personalized rehabilitation. In addition to fall risk assessment, the project may
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ecology, and/or restoration ecology. Experience in design, execution and analysis of acoustic data is desired. Knowledge on statistical methods and their application is an extra merit. Good knowledge in GIS
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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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efficiency, flexibility, and sustainability. Within this research project, Linköping University is collaborating with leading industrial companies to develop digital analysis and decision-support tools