Sort by
Refine Your Search
-
Category
-
Employer
-
Field
-
problems. This level of complexity increases when considering the multi-period operation of the system. These are difficult to solve using traditional strategies, so in recent years machine learning
-
, data scientific or machine learning background that is keen to work in an interdisciplinary environment and open to collaborating with researchers from other disciplines. The successful candidate will
-
of the project is to use machine-learning assisted molecular dynamics simulations incorporating quantum effects for the identification of new variant-specific drug targets which will be validated experimentally
-
Mines Paris - PSL, Centre PERSEE | Sophia Antipolis, Provence Alpes Cote d Azur | France | 2 months ago
-focused learning" or "End-to-end learning". For example, end-to-end machine learning (ML) models can be trained to minimize the downstream decisions regret or even directly learn a mapping from data to
-
/technical challenges Project FITNESS will build upon and extend state-of-the-art methods [1], [2] recently developed within the team, showing to outperform existing, machine-learning based approaches in
-
(FL) is a promising paradigm that is gaining grip in the context of privacy-preserving machine learning for edge computing systems [1]. Thanks to FL, several data owners called clients (e.g
-
the field of algorithm configuration and selection in a streaming fashion by investigating techniques that continuously optimize machine learning models as new data instances arrive [2]. A key focus will be
-
Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | 3 months ago
processing tasks, including machine learning and deep learning [4]–[6], database processing [7], [8], and networking [9]. Near-memory computing (NMC) is a memory-centric computing paradigm that has emerged as
-
-I) for the NASA HWO project. Additionally, you will benefit from the support of the Machine Learning “Centre de données Astrophysiques de Marseille” (CeSAM). The Laboratoire d'Astrophysique de
-
on individualised data; (2) to speed up FE model computation through machine learning prediction, in order to make it usable in clinical routine; (3) to conduct experimental validation of FE prediction results, in