Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- CNRS
- Eindhoven University of Technology (TU/e)
- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
- AITHYRA GmbH - Research Institute for Biomedical Artificial Intelligence of the Austrian Academy of Sciences
- Amsterdam UMC
- COFUND QuanG
- Constructor Knowledge Labs gGmbH
- Delft University of Technology (TU Delft)
- Fondazione Bruno Kessler
- Heidelberg Institute for Theoretical Studies (HITS gGmbH)
- Inria, the French national research institute for the digital sciences
- Technical University of Denmark
- The University of Newcastle
- Universitat Politècnica de Catalunya (UPC)- BarcelonaTECH
- 5 more »
- « less
-
Field
-
of thermal effects on force generation, material properties, and geometric clearances. Validate numerical models against experimental results and data available in the scientific literature. Disseminate
-
disturbances. Current control methods generally rely on simplified interaction models based on constant aerodynamic coefficients, quasi-static approximations, potential flow models, or experimentally identified
-
Skills/Qualifications Technical Skills: Advanced programming in Python, PyTorch, PyTorch Geometric or DGL. Version control (git), Linux and model training on GPU (reproducible experiments). Other
-
Model over that pipeline — a model that does not just generate code, but predicts the consequences of an architectural decision: total cost of ownership, unintended side effects, latency and failure
-
AITHYRA GmbH - Research Institute for Biomedical Artificial Intelligence of the Austrian Academy of Sciences | Vienna, Virginia | United States | about 14 hours ago
(e.g. geometric deep learning, generative models, representation learning) to decode molecular physiology, pathology, and therapeutic design? Are you passionate about high-throughput biology and scalable
-
translated into the underlying mathematical models. They may, for example, arise from perturbations in boundary conditions, input parameters, or geometrical properties. When neglecting the influence
-
of Josephson junctions. The methodology combines TEM, geometric phase analysis (GPA), chemical analysis (EDX), and growth modeling. Experiments using 4D-STEM coupled with electron ptychography will provide
-
companies. The research will integrate techniques of numerical analysis and structure-preserving algorithms to generative modeling in AI. It will build upon the work done at IMF and SINTEF in this field. We
-
of the proposed PhD are: (i) To investigate novel neural scene representation methods and their complementary with respect to conventional geometric methods (ii) To develop methods to decompose raw 3D scenes
-
30th September 2026 Languages English English English We are looking for a PhD candidate in Structure-preserving Generative Modeling Apply for this job See advertisement This is NTNU NTNU is a broad