Sort by
Refine Your Search
-
Country
-
Employer
- Delft University of Technology (TU Delft)
- National Energy Technology Laboratory (NETL)
- Chalmers University of Technology
- Eindhoven University of Technology (TU/e)
- KTH Royal Institute of Technology
- Carnegie Mellon University
- Cornell University
- King Abdullah University of Science and Technology
- University of Twente (UT)
- University of Washington
- Washington University in St. Louis
- Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association
- Massachusetts Institute of Technology
- Oak Ridge National Laboratory
- Southern University of Science and Technology
- Texas A&m Engineering
- University College Cork
- University of Illinois Chicago
- University of Twente
- VIB
- Wroclaw University of Science and Technology
- 11 more »
- « less
-
Field
-
chain, ranging from synthesis, cell assembly, characterization, modeling to scaled-up manufacturing. The 2-year postdoctoral project Machine Learning-based Electro-Chemo-Mechanical Estimation and Control
-
spans computational materials design, catalysis, energy materials, machine learning, and artificial intelligence. We offer a collaborative and international research environment with close interactions
-
cardiovascular care. Within the consortium, TU Delft contributes expertise in cardiac mechanics, soft tissue modeling, growth and remodeling, machine learning, and uncertainty-aware model personalization. As a
-
the CLARA AI agent — bridging cutting-edge machine learning methods with empirical insights from the educational arm of the project. A central technical challenge guides this position: How can an LLM-based AI
-
/communications, machine learning/vision, intelligent transportation systems, intelligent sensing/localization, or signal processing. In line with our Athena SWAN ambitions we especially encourage women to apply
-
at the atomic scale, using density functional theory-accurate machine-learned potentials and molecular dynamics simulations, in close collaboration with leading European research institutes and steel industry
-
, drawing on machine learning where it strengthens these methods. The research supports mission-critical scenarios and feeds into an end-to-end resilience proof of concept developed together with Swedish and
-
domains such as telecom, defence and cloud. You will join the Machine-Intelligence for Networks and Distributed Systems (MINDS) research group at the Department of Computing and Learning Systems, School
-
data and multimodal datasets combining imaging and molecular measurements. Have a background in computational biology, bioinformatics, or machine learning for biological problems. Have experience with
-
description Work on EU projects to develop next‑generation transport, emission and health forecasting models by integrating deep learning, xAI, and diverse data sources such as traffic sensors, smart‑card data