9 results
Postdoctorat de 36 mois à Grenoble dans le projet ANR BEAUT, à partir du 1er mars 2027. Les travaux exploitent les collisions plomb-plomb du Run 3 d’ALICE au LHC pour déterminer le transport des quarks lourds dans le plasma de quarks et de gluons. La personne recrutée développera un étiqueteur de jets de beauté par apprentissage automatique, mesurera leur…
Closes
Develop computational and mathematical methods for soil microbiomes in the Quince Group. The work combines long- and short-read metagenomics with metatranscriptomics, resolves strain diversity using statistical models, and supports predictive models of natural soils and synthetic microbial communities. The full-time appointment lasts three years, with…
Closes
Develop Bayesian calibration methods that explicitly represent model error in structural dynamics. The PLATON team will compare informative calibration quantities, implement and benchmark algorithms, and accelerate inference with surrogate models. The work aims to improve finite-element predictions under uncertain material, boundary and loading conditions.…
Closes
Develop machine-learning methods for quantitative neuropathology within the Brain Health initiative. Integrate histology, spatial molecular data, MRI and clinical information to investigate brain-disease mechanisms and progression. The role includes computer-vision models, multimodal learning, Bayesian and causal models, scientific collaboration and open…
Develop scalable machine-learning methods and infrastructure for the Brain Health initiative. Integrate digital histology, spatial transcriptomics, MRI and clinical data to model brain-disease progression at cellular resolution. Responsibilities include foundation models, distributed training, robust data pipelines and open-source scientific tools. This…
Develop multimodal foundation-model methods for gene regulation using modern deep learning, Bayesian inference and causal modelling. Work at the interface of computational research and large-scale biological data.
Develop computational methods for biological digital twins, including parameter estimation, uncertainty quantification, Bayesian inference and physics-informed neural networks. Build scalable simulation software and apply it with experimental and clinical collaborators to development and disease models.
Develop uncertainty-aware tunnel condition assessment from images, video, sensors and repeated three-dimensional scans. Fuse deterioration evidence through hierarchical Bayesian models, represent evidence quality and integrate indicators into a digital-twin prototype. The project includes underground inspection and validation with Hagerbach Test Gallery and…
Develop risk-based inspection and maintenance planning for tunnels. Combine practitioner interviews with Bayesian risk models, value-of-information analysis and optimization of intervention programmes under access and resource constraints. Validate methods with partners at Hagerbach Test Gallery and EuroTube. Screening starts 9 November 2026; applications…
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