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Field
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use tools from dynamical systems (deterministic and stochastic) and information theory. The bulk of the tasks will be dedicated to the study of bacterial cells, but it may also include the analysis
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build using molecular dynamics, the MACE foundation models and density functional theory. Main Tasks and responsibilities: AI4LSQUANT aims to accelerate quantum modelling by learning fast, accurate
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Properties of Nanoscale Materials group (GTNaM), active at the UAB since 2000, has become affiliated to the ICN2 in January 2021. Its activities mainly revolve around the study of thermal properties
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, nuclear physics and technology , Phenomenology , Physics High-Energy Theory / Collider physics , Neutrino physics , Particle Physics , Astroparticle Physics Appl Deadline: 2025/11/30 11:59PM (posted 2025
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networks and transformers. Practical experience with density functional theory (setups, convergence, interpreting outputs). Strong Python and deep-learning stack (preferably PyTorch); good software practices
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knowledge. The focus of the project can be defined in collaboration with the supervisor, with potential avenues including optimization aspects, parameter-efficient adaptation methods, model merging theory
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Infrastructure? No Offer Description Research line: Learning in single cells through dynamical internal representations. Job description: Develop theory, models and algorithms for identifying molecular encodings
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, Physics, Computational Chemistry, Nanoscience, Chemical Engineering, or a related field. Strong background in modelling (electro)catalytic processes using periodic density functional theory (DFT) is
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microscope, scanning tunnelling microscope, etc For more information about the QTWIST Program: https://qtwist.icfo.eu . Share this opening! Use the following URL: https://jobs.icfo.eu/?detail=890
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the scientific literature relating to (and around) the project · To undertake any necessary training · To learn and develop new research skills outside own discipline · Any other reasonable duties commensurate