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Field
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Mobasher. It involves a diverse range of activities including: structural and geotechnical modeling, machine-learning model development, structural sensing and health monitoring, conducting physical
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. The candidate is expected to: Advance cutting-edge knowledge on the electronic structure of spin-crossover systems with higher nuclearity Adquire advance knowledge in coordination chemistry Develop strong
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. Our research integrates clinical, neuroimaging, physiological, and immunological data to advance mechanistic models of severe mental illness. Relevant links: https://tmu.pure.elsevier.com/en/persons
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photosynthetic membranes. Specifically, pump-probe ultrafast nanoscopy of transport in model OPVs and light-harvesting complexes. Specifically, advance structured excitation methods for low light level exciton
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the command line. Background in structural biology, molecular modeling, protein dynamics, and understanding of ensembles. Have experience with large-scale computations on compute clusters, bonus points
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by the CNRS, the postdoctoral researcher will be responsible for contributing to the development of advanced methodologies for predicting crystal structures (CSP) based solely on their chemical
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, or related field - Expertise in advanced quantitative/statistical methods (e.g., generative computational modeling, multilevel and/or structural equation modeling, univariate and/or multivariate fMRI
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(AI), mechanistic modeling, and quantitative systems pharmacology (QSP). Funded by an NIH R01, our group develops predictive frameworks that integrate advanced AI/ML methods with multiscale mechanistic
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quantitative systems pharmacology (QSP). Funded by an NIH R01, our group develops predictive frameworks that integrate advanced AI/ML methods with multiscale mechanistic models of disease biology and drug action
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electrogravimetric response. To do this, we will implement a multi-stage approach, combining the development of model electroactive materials, their physico-chemical characterisation, and the advanced exploitation