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application! Work assignments Our research projects focus on distributed sensing, hardware-efficient signal processing, robustness and resilience, and communication-efficient decentralized machine learning
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or a related discipline A solid background in climate and atmospheric sciences, and extreme weather ideally supported by knowledge of machine learning and time series analysis is of advantage, as is
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leverage graph structures to represent, integrate and analyze multi-modal data, employing advanced machine learning techniques to address complex questions in biology. The team is focusing on different
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estimators, or machine learning) or other advanced statistical modelling. Advanced programming skills in Stata, R, Python or a similar software. Strong academic background with publications in international
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Pneumatic Tires, Structure-Process-Properties Relationships. How will you contribute? Do you have proven skills in data analysis, machine learning, as well as in mathematical and computational modelling? You
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The postdoc fellow will conduct research in the intersection of AI/Machine Learning and Software Technology. The advertised position will be placed in the DISTA research group (https://lnu.se/en/dista
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Experience in operating CVD, sol-gel, spin coating, Thermal evaporating machine, and hydrothermal reactor for the synthesis of quantum dots. To synthesize quantum dots in different inert atmospheres
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on machine learning solutions and data visualisation. In addition will some cod individuals be tagged, and their behaviour be monitored using acoustic telemetry. The cod behaviour could also be correlated with
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machine learning methods, including symbolic regression and neural networks. You will apply the algorithms to the discovery of new models in different fields, including robotic control, fluid mechanics and
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have expertise and experience in executing density functional theory (DFT) calculations, microkinetic modeling, kinetic Monte Carlo simulations, and Machine learning methods. Minimum Qualifications: Must