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Inria, the French national research institute for the digital sciences | Saclay, le de France | France | 2 months ago
(or surrogate models) are approximations of classical numerical solvers with a very low computational cost. They form the core of a digital twin. Using machine learning techniques to build these meta-models
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longitudinal within-person models, discrete-time survival analysis, and/or explainable machine learning. Each of the three work packages is designed to result in one publication, together constituting a
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). Development and validation of machine learning models for calculating occupational health indicators. Integration, management, and analysis of data from wearable monitoring devices. Experimental evaluation
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; - Development of a simulation module for parcel delivery operations, integrating traditional simulation techniques with Machine Learning models; - Development of algorithms for the integration of Machine Learning
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systems are generally ill-conditioned. The project sits at the intersection of classical numerical analysis, scientific machine learning and computational chemistry. Based on regularization techniques and
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 2 months ago
by LA/P/0083/2020 and 1801P.01460.1.06 LARSYS/ISR BASE 2025-2029 – LASEEB/ISR, financed by national funds through FCT/MCTES Workplan: The scholarship holder will acquire electrophysiological data (EEG
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-preserving machine learning (e.g. proving model integrity or fairness without revealing training data) Scalable ZK-proof constructions for federated and decentralised AI pipelines Formal security analysis
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flat interconnect AI compute clusters. Machine learning clusters and artificial intelligence (AI) training have become increasingly popular in recent years. The recent introduction of OpenAI’s ChatGPT
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31.07.2026, Academic staff We are seeking a researcher in Scientific Machine Learning (SciML) to join the project "Data science at scale" at the Technical University of Munich, Germany. Ideal
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. The research will involve training machine-learning models on large structure and sequence datasets and integrating membrane-specific biophysical constraints to enable the design of membrane proteins and