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Your Job: This PhD project focuses on modelling and simulating future gas grids, exploring transformation pathways, and developing cross-sectoral simulation frameworks to support informed decision
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receptors (GPCRs) using molecular dynamics simulations. The project will involve the application of standard and enhanced sampling techniques (including coarse-grained simulations) to: Characterize GPCR
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workflows for descriptor based microstructure reconstruction to identify material parameters for crystal plasticity simulations from experimental data through inverse analysis to establish structure–property
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partner from data sciences provides data management and AI based Image analysis, an internal experimental group, and an internal simulation-sciences group (You+Supervisor+support by lab
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talented and motivated applicants for PhD positions. As a member of our team, you will have the opportunity to collaborate on cutting-edge technologies like quantum simulators, Bose-Einstein Condensates, and
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edge of energy systems and computational engineering, developing scalable methods to simulate and secure IBR-dominated grids. Your key responsibilities include: Conducting large-scale simulations
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), uncertainty quantification, and atomistic simulations within the FNR-funded UMLFF project. MLFFs have transformed atomistic simulations, offering quantum-chemical accuracy for large systems. However, they
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through theory and simulation and/or experimental design and testing; developing new image reconstruction algorithms for providing more information with less radiation; and applying our techniques
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that are submitted into this UAB system will be considered: https://seleccio.uab.cat/ Please submit the following information to the indicated webpage: 1. Motivation letter (1 page). 2. CV (your preferred format and
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support for process development from laboratory to pilot to demonstration scale Working with a wide range of simulation tools such as CFD, numerial optimisation and artificial intelligence Topic-independent