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the research work that led to the attribution of a PhD degree in an entity other than the host unit (Institute for Sustainability and Innovation in Structural Engineering, ISISE); Do not exceed, with
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shapes. Motivating examples include the spatio-temporal dynamics of sweat droplets, interacting cellular or tissue shapes, and geometric structures arising in vegetation such as tree canopies. The work
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 3 hours ago
, their large-scale atmospheric structure, dynamical behavior and aurora and its coupling to the magnetosphere. The research will involve either data analysis of space telescope data (such as HST, JWST etc
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rolling basis with start dates as early as 1/1/2026 and as late as 3/1/2026. Group or Departmental Website: https://simpsoba.su.domains/ (link is external) How to Submit Application Materials: Please upload
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clearly across disciplines is essential. Personally, we value someone who is proactive, structured, and open to teamwork in a dynamic, international environment. You should be motivated to publish high
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At least 70% of your assignment will be spent on academic research with the main focus on studying the structure, dynamics, and intermolecular interactions of membrane-active lipopeptides using NMR
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-Saint-Aignan Cedex Website https://www.lab-cobra.fr/ https://www.univ-rouen.fr/etablissement/structures-de-formation-et-de-recherche/unites-de-recherche-et-de-service/carmen-institut-de-chimie-analytique
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an excellent publication record. Solid research experience in one or more of the following topics is expected: Graph neural networks Optimization algorithms Predicting structured output Self-supervised learning
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structures, interlocking forms and the notions of scale, while the temporal dimension is explored by reconstructing past trajectories through the study of forms, sedimentary fillings, natural and historical
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such as VASP, Quantum ESPRESSO, LAMMPS, GROMACS. • Machine-learned interatomic potentials. • Structure-property prediction using GNNs. • LLM fine-tuning and prompt engineering (e.g., HuggingFace, OpenAI