Sort by
Refine Your Search
-
of computer science, software systems engineering, digital technologies or comparable qualification Openness to varied and exciting topics and tasks in the field of digitized circular economy Independent, structured
-
if they do not exceed 25 percent of the total funding period and do not take place at the beginning of the programme The application for a scholarship follows a three-step process: Step 1: written application
-
computational physics and probability theory and great interest in interdisciplinary research and collaboration with experimental groups. You hold (or expect to complete soon) a Masters or equivalent degree in
-
-year contracts at each institution (4 in total) are envisaged. The applicant will have to apply and be admitted to post-graduate study programme at the Faculty of Mathematics and Physics, Charles
-
)physics, statistical mechanics, scientific computing and also a keen interest in interdisciplinary research and collaboration with experimental groups. You hold (or expect to complete soon) a Masters or
-
Master’s degree in Physics, Chemistry or Computer Science, or equivalent Interest in Physics, Chemistry and Machine Learning Good written and spoken English Ability to work both independently and in a team
-
applications ranging from Computational Physics, Computational Finance to Computational Electronics. For more details see https://acm.uni-wuppertal.de/en/ . A successful applicant is expected to have a
-
) and the German Academic Exchange Service (DAAD) since 2007. Under this CAS-DAAD joint programme up and coming young Chinese scientists from the University of Chinese Academy of Sciences (UCAS) and CAS
-
Biology, Biochemistry, Life Science, (Bio-)Physics, Chemistry, Computer Science, or related fields. Visit the IMPRS-LM website for more information about the program, the application process, and the
-
and performing laboratory (wind-wave facility) experiments, using state-of-the-art imaging techniques developing computational codes to process and understand large experimental datasets (e. g., image