Sort by
Refine Your Search
-
Category
-
Country
-
Program
-
Field
-
techniques and the structure of bilevel problems in large-scale settings. Objectives The goal of this postdoctoral project is to develop scalable blackbox optimization algorithms tailored to bilevel problems
-
suitable data models [CSC+23]. Objectives As far as the design of efficient numerical algorithms in an off-the-grid setting is concerned, the problem is challenging, since the optimization is defined in
-
older adults. The expected outcome is the creation of AI algorithms to detect early signs of neurodegenerative disorders in older adults living independently at home. The potential benefit is early
-
(morphological patterns), based on the experts’ knowledge. Then, tools like Procrustes analysis, linear dimensionality reduction (PCA) and standard clustering algorithms are employed. A first objective of our
-
the supervision of CNRS Terre & Univers, IRD, Université Grenoble Alpes (UGA), Grenoble-INP and INRAE. It employs around 330 people, including 190 permanent members (researchers, associate and full professors
-
, situated within the Institut Pasteur, is a collaborative unit involving Pasteur, INRIA, CNRS, and UPC. Led by a Principal Investigator (PI), Jean-Baptiste Masson, who is a theoretical physicist, the lab is
-
algorithms and deep learning models. Have proficiency in Python in a Linux environment and development experience using Tensorflow or PyTorch. Have strong linear algebra and computer vision knowledge. Have