Sort by
Refine Your Search
-
assurance Furthermore, collaboration with experimental and other theoretical groups in Vienna is desirable. Candidates should also actively contribute to and collaborate with the CRC TACO, https://sfb-taco.at
-
, or air pollutants. Our future research strategy also includes studies of the higher atmosphere. To learn more about our team, we invite you to visit our website: https://flexteam.univie.ac.at/ . To learn
-
qualitative social science research methods Demonstrable experience in mixed methods research Interest in the theoretical and philosophical aspect of mixed methods research Excellent command of written and
-
on the development and analysis of continuous and discrete models in connection with convex and nonconvex optimization problems and monotone inclusion systems. Our ideal candidate already has experience with modern
-
” research themes. The successful candidate will have: a PhD in Translation Studies/Machine Translation; practical experience conducting data-driven research in a machine translation/large language models (LLM
-
research areas, please visit https://isor.univie.ac.at/research/ . Ideally, your research interests should match or overlap with those of an existing working group at the institute. Your future tasks: You
-
philosophy of science, as well as ethics and philosophy of action. Further information can be found here: https://www.univie.ac.at/en/news/new-professorships/details/kraus-katharina https
-
organizational skills, with attention to detail and precision. Experience securing competitive research grants (desirable). What we offer: Work-life balance: Our employees enjoy flexible working hours, remote
-
apply a range of statistical methods to existing datasets or to data collected by own field observations and experiments. In addition, we have a focus on the development and application of predictive
-
areas of the group include stochastic processes, mathematical finance, and probabilistic transport theory. Our ideal candidate already has experience with modern methods in probability theory