76 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" uni jobs at Chalmers University of Technology
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at the division of Computer and Network Systems , where we design secure, dependable and high-performance computer and communication systems that meet the demands of an increasingly digital and interconnected world
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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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methods relying on machine learning, artificial intelligence, or other computational techniques. The applicant is expected to develop and apply data-driven and machine learning-based methods. Special
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complex behavior under demanding operating conditions presents a significant modeling challenge. This project addresses that challenge by combining machine learning with constitutive modeling, while
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equations, Bayesian inference, large-scale computational methods, bioinformatics, data science, machine learning, optimisation, numerical methods. Please read more about the position and our department on our
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cases, this can be slightly prolonged). The position will be placed at Timur Shegai's research group at Chalmers. You can find more information about the group at: www.shegai-lab.com or https
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percent of working hours Contract terms The Doctoral student positions is fully funded from start. The position is a fixed-term appointment of four years, with the possibility to teach up to 20%, which
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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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-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
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computational methodologies, ranging from atomistic and electronic-structure–based materials modeling and characterization, via machine-learning and high-throughput methods, to ab initio calculation