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realistic oxide nanoparticles with sizes from a few 10s of atoms to several 1000s of atoms. In each case, machine learned interatomic potentials (MLIPs) will be developed to describe their structure and
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ReDiLEEP training in response diversity methods, data management, reproducible code, R/Tidyverse, machine learning and AI for ecologists, visualisation, evidence-based policymaking, science-policy
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. Experience with finite element software development. Experience with machine learning and data-driven modelling. Experience with high-performance computing. Previous scientific publications. Qualification
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Python programming. ● Experience in monitoring code performance. ● 3 or more years of demonstrable experience in machine learning theory. ● Excellent communication and teamwork skills. ● Proficiency in
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University of Girona (UdG) - Institute of Computational Chemistry and Catalysis (IQCC) | Spain | 2 months ago
next-generation computational approaches to understand, predict, and engineer highly reactive intermediates in enzymatic catalysis. By combining quantum chemistry, molecular dynamics simulations, machine
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deployed. The research will therefore combine qualitative fieldwork with computational modelling to develop approaches that operate under uncertainty, adapt as the landscape changes, and generalise beyond