212 associate-professor-computer-science-"https:"-"https:"-"https:"-"https:"-"https:" positions at ETH Zurich in Switzerland
Sort by
Refine Your Search
-
2026, with a 100% workload, based in Zurich, and is fixed-term for three and a half years. Working across sociocultural, political-economic, and theoretical contexts, the LUS Doctoral Program fosters
-
policy, political economy, economics, sociology, computational social sciences, or a related field Strong knowledge of advanced quantitative methods is essential (e.g., econometrics, causal inference
-
psychology (preferably with an emphasis Cognitive or Educational Psychology), Learning Sciences, Cognitive Science, or a related field You should have a strong understanding of experimental design and
-
of Medical Microbiology at the University of Zurich, the Department of Informatics at ETHZ and several further partners, we address the challenge by the combining microfluidic technology, sequencing and fast
-
at the University of Zurich, the Department of Informatics at ETHZ and several further partners, we address the challenge by the combining microfluidic technology, sequencing and fast data analysis. In
-
Computer Science, Biomedical Engineering, Data Science, Cognitive Science, or a related field Strong Python programming skills and experience with PyTorch or TensorFlow Interest in multimodal data, time-series
-
convective heat transfer with the surrounding air. Within our research group at ETH Zurich, we are developing computational workflows for predicting temperature fields in machine tools using computational
-
is to build efficient and robust computational tools for analyzing complex engineering systems. Applications include structural dynamics and other dynamical systems relevant to real-world engineering
-
analysis tools for researchers Profile Degree in data science, computer science, Earth or atmospheric sciences, or a related field Knowledge of satellite data and remote sensing Experience with very large
-
operations that are yet to be fully understood. In this context, it is evident that the operation, control, and planning of power systems will soon be pushed to their limits. Therefore, new computational