-
with Simulation-based Inference ), funded by the Multidisciplinary Institute for Artificial Intelligence (MIAI) through an AIforScience Research Chair. ADACSI will develop a multi-probe simulation-based
-
Théorique (LAPTh, CNRS/Univ. Savoie Mont Blanc) invites expressions of interest for one or more postdoctoral researcher positions focused on advancing simulation-based Inference (SBI) frameworks for modern
-
determines observables of the replication program such as the Mean Replication Timing (MRT) and the Replication Fork Directionality (RFD) profiles. We proposed a strategy to train a neural network to infer
-
, integrating statistical inference, machine learning, and population genetics. We will develop advanced computational methods to characterize the functioning of T- and B-cell repertoires. The goal is to build
-
proficiency in techniques for quantifying inflammatory markers, including ELISA and related assays. Extensive experience in histology and immunohistochemistry, together with a proven track record in cell
-
analysis of the ATLAS experiment data. The L2IT team plays a driving role within the ATLAS collaboration for the reconstruction of charged particle tracks using geometric deep learning (GDL). The person who
-
/ live-cell imaging - Biological image analysis - Cell tracking - Cell culture - Quantification of biological data - Fiji / ImageJ · Statistical analysis 3. Desirable Skills - Centrosome dynamics