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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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, molecular assemblies — are out-of-equilibrium systems whose dynamics emerge from the coupling between stochastic fluctuations, internal forces, collective interactions, and geometry. Their quantitative
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spectroscopic techniques or molecular simulations is advantageous You have excellent communication and time management skills. In this international project team, excellent knowledge of English is essential, and
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materials. This project aims to change this and advance our understanding of the static and dynamic behavior of spins on surfaces and surface spin arrays. These systems, which represent real molecular quantum
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the transport and interaction of radiolytic species. To address this issue, the second approach will rely on molecular dynamics simulations using the LAMMPS code and ReaxFF empirical potentials, following
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integration, especially in molecular medicine; mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; causal inference and time
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. The key focus areas include: Displacement cascade evolution. Tracking microstructural evolution and defect dynamics. Investigating phase transitions under irradiation. Simulations of displacement-cascade
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). Our overall aim is to understand the molecular mechanisms of haematological cancers, and based on this; to design, develop and implement novel, scientifically based, clinical trials, with a strong focus
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and organ levels and cellular and molecular levels. The project will further develop a two-dimensional open source package for modeling plant tissues, called Virtual Leaf, which coupled a Hamiltonian
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integration, especially in molecular medicine; mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; causal inference and time