Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
demanding real-world geometries and to build specialist expertise in high order mesh generation, geometric modelling and CAD to CAE integration. These capabilities are of growing importance to industry yet
-
, robot control, unconventional cameras, humanoid robotics Skills: formalization of geometric and photometric image models, neural network training, software development, hardware installation, oral and
-
geometric and topological ML, neural ODEs/PDEs, reduced-order modeling, structure-preserving ML/AI, and optimization. This cluster hire consists of: Two (2) positions jointly appointed in the School
-
9 Feb 2026 Job Information Organisation/Company Université Gustave Eiffel Research Field Computer science » Modelling tools Engineering » Electrical engineering Researcher Profile First Stage
-
(“overparameterized”) machine learning models, like probabilistic graphical models, deep neural networks, diffusion models, transformers, e.g. large language models, etc. SLT is based on the geometrical understanding
-
consumption and turnaround time, placing increasing pressure on sustainability targets. Understanding how geometric changes influence the flow, thermal or structural response remains a major challenge, and
-
Model. Int. J. Hydrog. Energy 2014, 39 (9), 4516–4530. https://doi.org/10.1016/j.ijhydene.2014.01.036.  ; [3] Carral, C.; Mele, P. Modeling the Original and Cyclic Compression Behavior of Non-Woven
-
primary research aim will be to explore how the geometry of data can help build better uncertainty-quantifying models, particularly for complex data types like molecules and images. However, other research
-
., Random Forest Trees and related ensemble models) to identify key controls governing catalytic performance. You will work closely with experimental collaborators to interpret spectroscopic and catalytic
-
more cost-efficient. Together, UESL and IMOS are seeking a motivated and qualified PhD candidate to advance the use of hierarchical graph neural networks for modeling multi-scale urban energy systems. By