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contacts with other disciplines nearby and interacts with biomedicine, pharmacy, physics and materials science. Scientists with expertise in biophysical methods of interaction analysis are responsible for a
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provides excellent access to research infrastructure, including databases, computational facilities and instrumentation, as well as to clinical materials and networks and training activities. The four
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, computational facilities and instrumentation, as well as to clinical materials and networks and training activities. The four laboratories of the partnership adhere to the EMBL model for research organisation
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, computational facilities and instrumentation, as well as to clinical materials and networks and training activities. The four laboratories of the partnership adhere to the EMBL model for research organisation
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, computational materials science, computer science, or a related field, awarded no more than three years prior to the application deadline*. Background in physics-based battery modelling and/or machine learning is
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qubits (i.e. the building blocks of the quantum computer) —caused by ionizing radiation from cosmic rays and radioactive materials— which tend to be correlated and cannot be corrected using existing error
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fields: materials engineering or science, mechanical engineering, electrical engineering, optical engineering, nanotechnology, or equivalent. Experience with drawing of optical fibers especially hollow