Sort by
Refine Your Search
-
Listed
-
Employer
- Nature Careers
- Inria, the French national research institute for the digital sciences
- CNRS
- IRIT, Université de Toulouse
- American University of Paris;
- CEA
- IMT - Institut Mines-Télécom
- IMT MINES ALES
- IMT Mines Ales
- Institut National Polytechnique de Toulouse
- Institut Neel
- Laboratoire National de Métrologie et d'Essais - LNE
- NIMES UNIVERSITE
- The American University of Paris
- UNIVERSITE DE TECHNOLOGIE DE COMPIEGNE
- Université d'Orléans
- Université de Caen Normandie
- Université de Lorraine
- Université de Technologie de Belfort-Montbéliard
- Université de Toulouse
- université Strasbourg
- École nationale des ponts et chaussées
- 12 more »
- « less
-
Field
-
for simulating such complex geometries. For example, the memory and computation time required become prohibitive with standard “black-box” finite element methods. The objective is therefore to develop a dedicated
-
work will be organized around the following areas: 1. Bee detection and tracking: Development of computer vision algorithms to identify and track each bee from high-resolution images, while
-
train robust machine learning (ML) algorithms without exchanging the actual data. The benefits of such a decentralized technology over personal and confidential data are multiple and already include some
-
. The monitoring of telecommunications and energy production and distribution networks are characteristic examples of such time-critical applications. The project aims to propose unsupervised online CPD algorithms
-
, sensor failures, or the aggregation of datasets from multiple sources. There is a rich literature on how to impute missing values, for example, considering the EM algorithm [Dempster et al., 1977], low
-
connected and valued on their academic journey. Internationally recognised research drives innovation in digital transformation, health, and sustainable development. This scientific progress is supported by
-
proof of excellence in teaching. They should show expertise in their specific area and experience in Data Science and/or Software development, including academic publications and contributions
-
algorithms will be developed to extract discriminative and predictive features from a multimodal dataset consisting of digital histopathological images, lung CT images, clinical, genomics, and multiproteomics
-
behaviours. Various methodologies have been developed, including physics-informed ML approaches that use numerical modelling to create synthetic datasets (e.g. Tristani et al., 2025). Additionally, approaches
-
modeling the dynamic of the data evolution is clearly important. The purpose of this postdoc position, within the Institut 3IA Côte d'Azur (Univ. Côte d’Azur & INRIA), will be focused on the development and