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closed loop , by feeding back the decisions into the processes when their criticality allows such unsupervised behavior. Conventional machine learning models suffer from significant limitations in both
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The Machine Learning for Integrative Genomics team at Institut Pasteur, headed by Laura Cantini, works at the interface of machine learning and biology, developing innovative machine learning
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laboratory team is likewise highly recognized for its research in computer vision and neuro-inspired artificial learning. Both teams have been collaborating for four years on projects at the interface between
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transfer learning to transpose the recurrent neural network (RNN) model available for supercritical CO2 power cycles to other cycles. Since thermodynamic conditions vary greatly depending on the fluid and
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 16 days ago
applications have been organized in different steps that interact with each other. The classical first step is to describe the application through a model. Through this model, a first process is operated
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via thermodynamic power cycles. However, conventional expansion machines (turbines or volumetric devices) face significant limitations at low power scales: - Turbomachinery suffers from reduced
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of Communities team and interact with its members. The modeling work will also involve collaborations with researchers from CEFE (Montpellier), BIOGECO (Bordeaux), and forest management partners (ONF). Our little
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of the landscape over time. The LANDIS-II forest landscape disturbance and succession model will be used to perform simulations based on palaeoecological data. The student will collaborate with project researchers
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be done via computer simulations, including Monte Carlo and molecular dynamics, combined with the use of statistical mechanics to predict e.g. phase transitions, nucleation rates, etc. The work will be
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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