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Field
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of extensive datasets. You will be supervised researchers who collectively offer expertise in computational biology, genetics, epidemiology, and machine learning. The research will be closely linked
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-energy devices. Using state-of-the-art electronic-structure calculations and machine learning methods, you will model these effects and contribute to the design of improved semiconductors for solar cells
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modeling, differential equations, Bayesian inference, large-scale computational methods, bioinformatics, data science, machine learning, optimisation, numerical methods. Please read more about the position
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machine-learning and high-throughput methods, to ab initio calculation of electrochemical reaction kinetics. The position is funded by the Swedish Energy Agency’s research program “Sustainable Battery Value
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of prior learning. For other eligibility requirements, refer to Karlstad University’s Appointments Procedure . Assessment criteria In the assessment, equal weight will be given to teaching expertise and
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electronic systems. You will also develop and teach courses in electronics design at the bachelor and master levels, and take part in the further evolution of the excellent and multi-faceted research and
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access to preventive care and neighborhood characteristics influence long-term health trajectories. The project applies both econometric and machine learning approaches to identify high-risk groups and to
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Master's degree in computer science, computer engineering, or equivalent. Demonstrate proficiency in English (reading, writing, speaking). Show the ability to work independently and in a team, as
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. Teaching may also be included, but up to no more than 20% of working hours. The position includes the opportunity for three weeks of training in higher education teaching and learning. The purpose
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-disciplinary research at the intersection of artificial intelligence, robotics, machine learning, and human-robot interaction. Subject area The subject area for this position is Computer Science. Background