53 machine-learning "https:" "https:" "https:" "https:" "https:" positions at Chalmers University of Technology in Sweden
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on the 25-qubit device. Project 2: Machine Learning for Quantum Transpilation This project aims to bridge the gap between idealized quantum circuits and physical hardware constraints. ML Architecture: Develop
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Experience in machine learning for neural data What you will do Take courses at an advanced level within the Graduate school of Electrical Engineering ( Graduate schools | Chalmers ) Develop your own
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measurement technique development, atmospheric modelling, and advanced methods for integrating observational and model data through data assimilation and machine learning. About the research project The overall
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Do you want to learn how to do machine learning on a real quantum computer, with application to real problems from Life Science? About us The Wallenberg Centre for Quantum Technology (WACQT ) is a
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Chalmers and Volvo Car Corporation. Who we are looking forThe following requirements are mandatory: a Master's degree (masterexamen) of 120 credits or a Master’s degree (magisterexamen) of 60 credits* in
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: Experience in microwave measurements Experience in Artificial Intelligence and Machine Learning methods for microwave circuit design Experience in digital signal processing What you will do Take courses
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for documented circumstances such as parental leave or military service. You have demonstrated independent, high-quality research and show strong potential to build an internationally competitive research program
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to the seven-year eligibility limit may be made for documented circumstances such as parental leave or military service. You have demonstrated independent, high-quality research and show strong potential
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parental leave or military service. You have demonstrated independent, high-quality research and show strong potential to build an internationally competitive research program. We also expect you to have
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measurement technique development, atmospheric modelling, and advanced methods for integrating observational and model data through data assimilation and machine learning. About the research project The overall