148 machine-learning "https:" "https:" "https:" "https:" "https:" "Cardiff University" positions at Chalmers University of Technology in Sweden
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computational costs by orders of magnitude and enabling breakthroughs in drug design and materials science. The position bridges machine learning and molecular science, with opportunities for collaboration
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background. However, for this project you must also be open to learn to include social science perspectives on the energy transition by means of cooperation with other research groups. Who we are looking
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technology, and to build a Swedish quantum computer). Within AQP, the group of Anton Frisk Kockum has the overarching goal of providing humanity the tools to understand and use large quantum systems. Working
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your application: Experience in system identification and machine learning is a merit. What you will do Perform research, developing your own scientific concepts and communicating the results of your
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machine learning on large epidemiological cohorts, diet and health data analysis of omics data (metabolomics, proteomics, microbiome, etc.) development of predictive models and digital decision-support
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initiative started in 2018 with the purpose of advancing Swedish academia and industry to the forefront of quantum technology, and to build a Swedish quantum computer). For the research on quantum optics with
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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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the last three years prior to the application deadline. Experience in some of the following areas is meritorious: AI and machine learning; convex analysis; functional analysis; mathematical statistics
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, or quantum-inspired methods Experience with hybrid quantum–classical algorithms or optimization methods Background in uncertainty quantification, reduced-order modeling, or machine learning Experience
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-order modeling, or machine learning Experience collaborating in interdisciplinary research teams What you will do Develop hybrid quantum–classical methods to improve simulation and prediction