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Field
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property prediction, modern artificial intelligence methods, molecular dynamics, and interdisciplinary research, this is your chance to be part of an exciting journey at the forefront of science and
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dynamical systems theory, including differential equations, simulation techniques, state-space and input-output representations, time-delay embedding, and/or time series analysis from experimental data
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(ab initio calculations, Molecular dynamics, Computational modeling) and materials science. - Excellent skills and understanding in physical-chemistry of materials. - Excellent verbal and written
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CFD methods DFT and Molecular modelling linked to CCUS Strong analytical and problem-solving skills, with an ability to interpret and analyze simulation and/or experimental results. Ability to work in
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of tomorrow and creating novel solutions to major global challenges. Our community is made up of 13 000 students, 400 professors, and more than 4 500 other faculty and staff working on our dynamic campus in
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setting. Conduct process simulations using tools such as Aspen Plus, COMSOL, or equivalent software to predict system performance. Collaborate with engineering companies to develop a prototype carbon
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Postdoctoral Associate Required Qualifications: (as evidenced by an attached resume) ● Doctoral degree (or foreign equivalent) in Molecular Biology, Cell Biology, Genetics, or a closely related
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Postdoc (f/m/d): Machine Learning for Materials Modeling / Completed university studies (PhD) in ...
to collaborative software development and version control systems (Git) # Experience with electronic structure and molecular dynamics simulation codes (VASP, QuantumEspresso, CP2K, LAMMPS) # Motivation to work
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proficiency in Density Functional Theory (DFT) and/or Molecular Dynamics (MD) simulations, enabling the computational investigation of material properties, electronic structure, and atomic-scale behavior
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Chemical engineering or a related field. Extensive experience in unit operations and chemical processes. Ability to conduct experiments. Experience in using both steady-state and dynamic modeling, simulation