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identification and machine learning. The key challenge is striking a balance between, on the one hand, modelling the physical, dynamic and nonlinear behavior of the components with sufficient physical accuracy
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Arts et Métiers Institute of Technology (ENSAM) | Paris 15, le de France | France | about 12 hours ago
Offer Description Funding: 36 months, CIFRE (https://www.anrt.asso.fr/fr/le-dispositif-cifre-7844 ) Starting date: November / December 2025 Keywords: Physically informed machine learning, Industrial
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 1 hour ago
on MMS data. Required Knowledge, Skills & Abilities: Computer analysis of digital data from satellite data centers. Physics background analyzing the data. Other Requirements: local residency. Preferred
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and small, contribute to a better world. We look forward to receiving your application! Your work assignments We are looking for one PhD student working on generative AI/machine learning, with
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financement Where to apply Website https://www.abg.asso.fr/fr/candidatOffres/show/id_offre/133293 Requirements Specific Requirements Etudiant(e) titulaire d'un Master II en Statistique / Machine Learning
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application! Your work assignments We are looking for one PhD student working on generative AI/machine learning, with applications towards materials science. Generative machine learning models have emerged as a
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. Fe, S) on CNT purity and structure. Evaluate CNTs as conductive additives in standard Li-ion battery electrodes. Apply AI/machine learning to optimise experimental design and growth parameters
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an exceptional international team with expertise in all aspects of the project. Your tasks will include: • Preparation of different EO and in-situ datasets for training a machine learning model • Development of ML
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analysis Background in biomedicine and digital pathology What we offer Embedding within a computational team, with extensive experience in computational biology and machine learning. Embedding within
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analysis Background in biomedicine and digital pathology What we offer Embedding within a computational team, with extensive experience in computational biology and machine learning. Embedding within