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the development of hierarchical computational materials discovery schemes combining random structure searching, machine learning, atomistic, and density functional theory (DFT) calculations to accurately and
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superconducting qubits and millikelvin electronics Did you recently get your PhD in circuit quantum electrodynamics (cQED) and are now looking into taking the full potential of your skills into use for making new
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this suits a candidate with a background in optical systems / imaging, or with more experience in machine vision, or systems control and automation, or data interpretation. A candidate would not be expected
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bioinformatic workflows. Familiarity with biomedical ontologies and text mining on Electronic Health Records and biomedical literature Knowledge of machine learning / deep learning with an interest in
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matching post based at Teesside University); (3) nature and natural heritage (the focus of a matching post based at Newcastle University); (4) active evaluation for learning (e.g. research conducted by team
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at Université Paris-Saclay (https://cvn.centralesupelec.fr/ ), Prof. Pock from the Institute of Computer Graphics and Vision at Graz University of Technology (ICG ), Prof. Thiran from the EPFL Signal Processing