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Field
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development. The successful candidate will contribute to the development of deep learning methods to predict reaction outcomes and optimal reaction conditions for organic reactions. The work will involve model
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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
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models combined with the finite element method. Constitutive relations are required to describe material behavior. Advanced stainless steel typically possess complex microstructures across various length
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at the Niels Bohr Institute, Faculty of Science, University of Copenhagen. We are located in Copenhagen. We offer creative and stimulating working conditions in a dynamic and international research environment
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with host bacteria during infections, particularly focusing on the use of E. coli and its related phages as model organisms. However, the results may be applied in pathogenic bacteria related to E. coli
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conversion reactions. The second position is focused on modelling stability of electrocatalyst materials. The aim is to develop a framework to predict metastability of catalyst materials. Among the methods
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courses on quantum field theory and the Standard Model of particle physics.) Or you expect to obtain your Master’s degree around the starting date of the appointment. You are curious, communicative
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The project: We invite applications for a fully funded PhD studentship in the Solid Mechanics Group at the University of Bristol to work on the predictive modeling of hydrogen-induced damage in
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-edge interdisciplinary project aims to understand charge transport in the natural mineral feldspar, unlocking new ways of measuring the rates of Earth surface processes — from weathering and erosion
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courses on quantum field theory and the Standard Model of particle physics.) Or you expect to obtain your Master’s degree around the starting date of the appointment. You are curious, communicative