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language processing, and more. We own and operate the entire technology stack for Machine Learning Operations. This ensures that the models we build translate into secure, reliable, and actionable outcomes across
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math, biomedical engineering, physics, or related discipline. Proficiency in programming and data science tools (Python, R, C++, or equivalent). Strong statistical and machine learning background, with
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of results at conferences - interaction with team members and international collaborators The Machine Learning for Integrative Genomics team (https://research.pasteur.fr/en/team/machine-learning
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) training personalized computational models in new contexts, and (iii) studying in-silico clinical intervention strategies. The postdoctoral fellow will have the opportunity to: Learn about computational
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Your Job: Investigate current challenges and bottlenecks in power flow analysis for large scale electrical distribution grids Apply machine learning/AI or surrogate modeling (e.g., neural networks
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Proficiency in at least one programming language, preferably Python; experience with scientific computing, numerical modeling, or machine-learning frameworks is an asset Strong analytical skills with a solid
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computing systems design and realization, including machine learning (ML) and artificial intelligence (AI) applications including autonomy, sensing and communication, advanced manufacturing, and decision
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sustainability. The selected researcher will contribute to the development of predictive models and machine learning algorithms for data analysis from plant-based sensors, multispectral and thermal imagery, and
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harmonization, multi-omics integration as well as the development of machine-learning models for patient stratification and outcome prediction. Moreover, complex multi-layered datasets shall be integrated
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 10 days ago
appreciated : Interest in privacy, data protection, or evaluation of machine learning models. Experience with reproducible experiments (code organization, documentation, version control) is appreciated