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processing using high-throughput experimentation (HTE), analytical tools and machine learning under CircuLab. The candidate will be dedicated to establish the unique functionality of the platform and should
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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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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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at the intersection of artificial intelligence, robotics, machine learning, and human-robot interaction. Project description The focus of the project is machine learning and specifically the development of novel neuro
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We invite applications for a Doctoral student position in applied mathematics and machine learning for urban 3D reconstruction, within the Digital Twin Cities Centre (DTCC). The project aims
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preparation (for example, questionnaires, interviews, etc) and processing (for example, machine learning etc) for the DSS, with related documentation. In OPTIX, contributing to the digital twin models