Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
writing and presentation skills. At the start of the PhD, having obtained a Master’s degree in a relevant field, such as AI, mathematics, physics, (computational) neuroscience, etc.. Terms and conditions
-
institutes in Berlin which are funded by the federal and state governments. The research institutes belong to the Leibniz Association. WIAS invites applications as PhD Student Position (f/m/d) (Ref. 25/11) in
-
which are funded by the federal and state governments. The research institutes belong to the Leibniz Association. WIAS invites applications as PhD Student Position (f/m/d) (Ref. 25/11) in the Leibniz
-
, engineers and PhD candidates. The PhD candidate is expected to develop an advanced engineering noise prediction model for efficient computation of sound propagation in a range-dependent atmosphere where
-
: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
-
Biology, Physics, Applied Mathematics, Computer Science, Bioengineering, Systems Biology or a related field. Proficiency in modelling using differential equations is required. Candidates must have
-
knowledge about natural resource management Knowledge of software R Strong skills and/or interest in mathematical and statistical modelling is a strength Ability to conduct field work in remote alpine areas
-
traders and technologists to push strategies into production What we're looking for PhDs graduating by Summer 2026 or postdocs in quantitative fields such as Mathematics, Physics, Statistics, Electrical
-
Biology, Physics, Applied Mathematics, Computer Science, Bioengineering, Systems Biology or a related field. Proficiency in modelling using differential equations is required. Candidates must have
-
: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create