Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
on close collaboration between the university and industry and aims to optimize processes, reduce error margins and increase productivity in the industrial companies involved in the project. Virtual models
-
optimization of imaging parameters. Overall, this project aims to explore, develop and integrate advanced imaging modalities towards their use for biological samples. Work tasks The main task of the position is
-
, design and characterization of quantum processors Development and optimization of nano-fabrication processes for large-scale devices Development of optimal control techniches to achieve fast and high
-
information is lost through this depreciated sampling frequency remains unknown. DETERMINER aims to determine the optimal sampling frequency for detecting externally driven phytoplanktonic change while also
-
into two main areas: (1) material development and characterization to ensure optimal sensing and mechanical performance, and (2) structural evaluation of SS-FRCMs under environmental stressors such as freeze
-
empirically validate how GenAI agents can assist software developers in tasks such as code generation, documentation, optimization, and human-AI interaction workflows. As a postdoctoral researcher, you will be
-
mechanics, numerical methods, microstructural mechanics, structural optimization, and experimental methods. The department also has strong activity in X-ray and neutron methods for materials research. Project
-
propagation problems, stochastic partial differential equations, geometric numerical integration, optimization, biomathematics, biostatistics, spatial modeling, Bayesian inference, high-dimensional data, large
-
learning can improve software architecture recovery, how to optimize machine learning models at compile and runtime, and autonomous agents for software development. Part of the research is conducted through
-
research questions. This postdoctoral scholarship offers the opportunity to be a part of this AI revolution by developing novel neural network architectures specifically optimized for plant genomic data. Our