Sort by
Refine Your Search
-
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
-
: 305,000 euros total funding over the project duration, including: • 199,000 euros for contractual collaborators (PhD students, postdocs, research assistants) • 106,000 euros for operational expenses
-
, transport, or defense. On the technical side, we aim at combining statistical latent variable models with deep learning algorithms to justify existing results and allow a better understanding of their
-
analyzed. The tensor model structure estimated by suitable optimization algorithms, such as that recently developed in [GOU20], will be considered as a starting point. • Exploiting data multimodality and
-
(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
-
biology, multi-scale imaging, and evolutionary cell biology. You will work closely with the group leader to coordinate and assist PhD students and postdocs in achieving the laboratory’s scientific goals. In
-
the use of synthetic data in precision medicine research and applications through development of AI algorithms, tools and other processes to allow for the enrichment of clinical data sets Providing training
-
machine learning or theoretical biophysics or computer science Conditions. Postdoc position funded by Centre Inria at Université Côte d’Azur, France. The position is located in Sophia-Antipolis, French
-
of the surgical procedure (direct filming and arthroscopic video feed), and a device for recording heart rate. In the second phase, the student will propose signal processing and data fusion algorithms to reconcile and
-
the ability of neural networks to learn unknown posterior distributions distributions. Their use in the field of image microscopy, however, remains limited. The purpose of this PhD thesis is to develop