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Want to combine your programming skills with pioneering research in Human-Robot Interaction? Join our multidisciplinary research team and gain practical experience developing software for robotic
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of engagement. Read more at: 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
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research environments in Computational Science, the research and education has a unique breadth, with large activities in areas such as numerical analysis, mathematical modelling, development and analysis
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of the world’s largest research environments in computational science, with large activities in areas such as machine learning, optimization, scientific software development and high-performance computing
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/JPL (https://costar.jpl.nasa.gov/ ). Subject description Robotics and artificial intelligence aim to develop novel robotic systems that are characterized by advanced autonomy for improving the ability
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genes, individuals and populations, to communities and ecosystems. We work within ecology, evolution, physiology, systematics and combinations of these fields in order to understand the impact of natural
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Lab at the Swedish University of Agricultural Sciences (SLU) in Uppsala, Sweden. The Yant Lab develops computational and genomic approaches to understand evolution, adaptation, genome dynamics, and
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description Work on EU projects to develop next‑generation transport, emission and health forecasting models by integrating deep learning, xAI, and diverse data sources such as traffic sensors, smart‑card data
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HIBEAM/NNBAR at ESS and – most relevant for this project – LDMX at SLAC (https://confluence.slac.stanford.edu/display/MME/Light+Dark+Matter+Experiment ). We exploit synergies across these projects, and our
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management. Our research addresses various aspects of strategy, design, planning and control, measurement and development of supply chains. Current research areas include supply chain preparedness and risk