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for Quantum Technology (WACQT, http://wacqt.se ). The core project of the centre is to build a quantum computer based on superconducting circuits. You will be part of the Quantum Computing group in the Quantum
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progression, machine learning. You will collaborate locally and internationally with groups in both theory and experiment. You will disseminate your findings by publishing in scientific journals and presenting
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of the PhD student will touch upon various topics multi-body dynamics, optimal control theory, machine learning and robotics and artificial intelligence in general. The focus is broadly upon the development
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iterative machine learning models with microbiological wet lab work. The second PhD position is planned to be wholly wet lab-based with a focus on microbiology and membrane biophysics. The project involves AI
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theoretical physics Some computer programming knowledge, e.g., Python, C/C++, Julia, etc. Strong written and verbal communication skills in English Experience in the following areas is beneficial but not
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/or reactor physics Documented knowledge/experience in machine learning What you will do As a PhD student, you will have the opportunity to shape your research project while receiving guidance and
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properties of superconducting circuits, both analytically and numerically. Familiarity with open quantum systems. Background in optimal control methods. Experience with machine learning for optimization
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a quantum computer based on superconducting circuits. You will be part of the Quantum Computing group in the Quantum Technology Laboratory (QTL) division of the Microtechnology and Nanoscience (MC2
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interaction combined with extensive field measurements. A digital twin of the detector will be created to train a machine learning model for predicting dynamic wheel loads. The overarching aim is to enhance
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methodologies, ranging from material characterization, via machine-learning and high-throughput methods, to ab initio calculation of electrochemical reaction kinetics. The position is part of the Chalmers Area of