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multi‑omics data. You will also partner with AI experts to integrate predictive models and advanced analytics into omics workflows. You will work in an expanding team led by Dr. Masoomeh Rahimpour
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models. Misclassification Characterization (Month 4-5) Construct an augmented misclassification dataset containing: original and perturbed variants, model predictions, correct labels, perturbation type
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intelligence as applied to trauma systems and acute care surgery. Fellows will engage in cutting-edge research spanning multiple domains, including risk prediction models for surgical complications, clinical
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Description In this project, we develop machine learning models for prediction of optical properties of chiral molecules based on DFT/CCSD data which we calculate ourselves. We include derivative information by
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pipelines that push technological boundaries for our clients. The Engineer will tackle complex challenges at the intersection of Large Language Models, Computer Vision, and Predictive Analytics while ensuring
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://www.nature.com/articles/s42256-021-00407-x), and extending these tools or developing new models as needed. The candidate will have the opportunity to work directly with experimentalists to validate predictions and
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hydrogenation, dehydrogenation, and hydrogen transfer reactions. Detailed characterization and kinetic studies will be performed to test computational predictions and microkinetic models, and to refine machine
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identification, i.e. learning of models from measured data, and iii) real-time control, e.g. using the model predictive approach. We are working on several projects with industrial partners across the energy
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AI researchers from ANITI, IMT and CERFACS, as well as with researchers/engineers in weather forecastings from the CNRM (Météo-France). Hybridization methods between neural networks and physical models
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an import element in the prediction of reactor-scale operational scenarios providing compatibility to both, required heat and particle exhaust constraints and good fusion plasma core performance. Given