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prototype system based on advanced commercial sensors for fall risk assessment and rehabilitation. The project includes both experimental sensor data acquisition and algorithm development. You will be
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Are you interested in developing computational tools to understand the detailed mechanical behaviour of multi-phase materials? Then this PhD position at Chalmers University of Technology might be
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• Perform genetic studies and bioinformatic analysis to identify genes and mechanisms that control these traits • Develop DNA markers for future application in plant breeding In the research studies, you will
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, optimization) or AI.- Someone who enjoys working in a team, takes initiative, and isn’t afraid to think outside the box.- Someone with excellent grades from BSc and MSc studies, and not afraid of experimental
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or predictive modelling of pathogen biology or host-microbe systems for which multidimensional, genome-scale experimental data are now available or it may use population-scale genetic, clinical, or public health
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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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molecular mechanisms that drive its invasive behavior, both general and patient-specific. Using cutting-edge spatial techniques and CRISPR-based methods, we build data-driven models that link gene regulation
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effort at the intersection of machine learning and applied mechanics. The focus of this position is on extracting information about what a neural network has learnt in a symbolic and (human) interpretable
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transformations of industrial importance. The PhD candidate will become a member of an enthusiastic interdisciplinary research team, which combines experimental and computational tools in the development of novel
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We are searching for a doctoral candidate eager to take part in crossdisciplinarity work within battery technology for a sustainable future. This work will compose both theoretical and experimental