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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 11 days ago
) Optimization and parameter identification methods Data-driven modeling and machine learning Physics-Informed Learning (or hybrid modeling approaches) Handling and analysis of large-scale datasets (e.g., mobility
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://www.maynoothuniversity.ie/physics/our-research . This position is part of the CARINA project which is funded through a Research Ireland Frontiers of the Future grant. CARINA stands for Combining Machine Learning with
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that combines modern machine learning approaches with large-scale biological data to automate genome curation by detecting, interpreting, and correcting structural errors, reducing manual effort from weeks
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: Applied mathematics; Machine Learning; Mathematical Modelling Appl Deadline: 2026/03/24 10:59 PM UnitedKingdomTime (posted 2026/03/18 04:00 AM UnitedKingdomTime, listed until 2026/04/01 04:59 AM
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publication record in sensing systems, mobile health, or HCI. Experience with signal processing, machine learning, or embedded systems is a plus. Carnegie Mellon University is an equal opportunity employer. It
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Union within the project “A Comprehensive Trustworthy Framework for Connected Machine Learning and Secure Interconnected AI Solutions (CoEvolution)”, - CUP F23C24000210006 – selection code: ipd_10D_0426_09/IINF
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worldwide and BNL is responsible for data compilation in North America. In order to make full use of the data in EXFOR, experience in data science, machine learning (ML) and applications of artificial
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hemocompatible coating strategies to improve membrane–blood interactions. - Model and optimize membrane performance using computational tools, machine learning, and artificial intelligence Work Plan - Synthesis
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quantitative and machine learning approaches ● Developing predictive models linking nuclear features to future cell fate ● Interacting with collaborators in imaging, computational biology, and developmental
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in Utah to recruit multiple postdoctoral fellows to apply high throughput methods and machine/deep learning to unlock the full potential of the dark proteome. Responsibilities Scientific visionRibosome