Sort by
Refine Your Search
-
quantitative medical imaging Proficient programming skills in at least one object-oriented language (e.g., C++, Python) and broad understanding of common programming paradigms, including object-oriented design
-
to contribute to sustainable development. To this end, scholarships are granted for development-related PhD studies for individuals who plan to pursue a career in teaching and / or research at the IIT in Delhi
-
of creative breakthrough." The methodology combines detailed case studies, comparative pattern analyses, and quantitative data evaluation with interdisciplinary perspectives from medicine, biology, chemistry
-
and development in the field of software engineering for dependable and safe automated driving systems. Conception, design, and implementation of software architectures and prototypes in
-
embodies a university culture that is characterized by cosmopolitanism, mutual appreciation, thriving innovation and active participation. For TUD diversity is an essential feature and a quality criterion of
-
. About your role: Develop improved physical models of the image formation process in holographic X-ray imaging Design and implement reconstruction algorithms for handling large-scale tomographic data from
-
materials. • Developing new methodologies in the field of nanofluidics. • Design and implementation of nanofluidic experiments with porous materials. • Publishing and presentation of scientific results
-
innovation and active participation. For TUD diversity is an essential feature and a quality criterion of an excellent university. Accordingly, we welcome all applicants who would like to commit themselves
-
University of Göttingen (Germany) and the European Synchrotron (ESRF) in Grenoble (France), we will design and build a novel synchrotron setup to combine x-ray scattering with light microscopy. The newly built
-
demands. To break this bottleneck and cut simulation time by orders of magnitude, you will design and implement surrogate models that learn the behavior of full‑physics codes using modern machine‑learning