Sort by
Refine Your Search
-
geosystems and spatial modeling of geomorphic processes as well as in the applied research in the thematic areas global environmental change, natural hazards and –risks, vulnerability, multi-hazard risk and
-
the area of chemoinformatics/modelling-based analyses of potential drug candidates and is looking for a scientist with expertise in this field. We are a committed and internationally leading team and offer a
-
, “human impact” on geosystems and spatial modeling of geomorphic processes as well as in the applied research including global environmental change, natural hazards and –risks, vulnerability, multi-hazard
-
, control theory and contemporary stochastic volatility modeling. The successful candidate will cooperate with the members of Christa Cuchiero’s group as well as with the associated research groups
-
to be coupled to model-free analysis of molecular dynamics simulations. This includes work in the biochemical wet-lab as well as with prototype NMR spectroscopy and computational tasks. You have previous
-
Biochemical Network Analysis group, led by Jürgen Zanghellini . The team focuses on mathematical modeling, artificial intelligence, and high-performance computing to study metabolic networks and optimize
-
human study populations and ideally including experience in advanced statistical modelling of indicators of diet and health. The successful candidate will have to coordinate his/her activities in teaching
-
models, time series, cross-sectional or network data, also in high-dimensional, high-frequency, and/or misspecified scenarios. Proficiency in modern data science methods and their applications would
-
. program and will work on the development and analysis of statistical methods for machine learning, particularly in the context of high-dimensional models and with a particular focus on methods such as
-
applicants for a 6-month paternity leave replacement who have a strong interest in using computational methods such as cognitive and psychophysiological modeling, (Bayesian) statistics and optimal experimental