Research Scientist
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Le poste
Line 1: Formulate and solve ambiguous materials and molecular discovery challenges by translating them into well-defined optimization or graph-based ML problems.
Line 2: Design, implement, and maintain data pipelines to collect, clean, and analyze structured and unstructured data from experiments and chemical databases.
Line 3: Develop predictive models and advanced deep learning approaches (GNNs, Transformers) for motif discovery and property prediction in material and molecular design.
Line 4: Leverage Generative AI and large language models to automate knowledge discovery and explore new formulations and synthesis routes.
Line 5: Define KPIs, evaluate model performance, and contribute to a Virtual Lab environment to validate research outcomes.
Line 6: Collaborate with chemists, materials scientists, and engineers to translate research into production-ready solutions and publish high-impact work.
Line 2: Design, implement, and maintain data pipelines to collect, clean, and analyze structured and unstructured data from experiments and chemical databases.
Line 3: Develop predictive models and advanced deep learning approaches (GNNs, Transformers) for motif discovery and property prediction in material and molecular design.
Line 4: Leverage Generative AI and large language models to automate knowledge discovery and explore new formulations and synthesis routes.
Line 5: Define KPIs, evaluate model performance, and contribute to a Virtual Lab environment to validate research outcomes.
Line 6: Collaborate with chemists, materials scientists, and engineers to translate research into production-ready solutions and publish high-impact work.
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