137 cloud-computing-"https:"-"https:"-"https:"-"https:"-"https:" positions at ETH Zurich
Sort by
Refine Your Search
-
Each doctoral student will lead a coherent subproject within this broader research program: Position 1: AI for Computational Thinking Focuses on designing and studying AI-assisted programming
-
collaboration with internationally leading groups in cell, organoid and computational biology. Profile PhD degree or equivalent in the fields of cell biology, mechanobiology, bionanotechnology, systems biology
-
computational mechanics to work on a project focused on the mechanics of colloidal systems. The PhD candidate will conduct research in a collaborative project with partners from the ETH Department of Materials
-
. You have a solid background in computer science, mathematics, or statistics and a strong interest in empirical analysis and interpretation. Areas of specialization can be, for instance, network analysis
-
100%, Zurich, fixed-term The doctoral program at the Institute of History and Theory of Architecture (gta), ETH Zurich, offers two fellowship positions to start on 1 October 2026. This program
-
component of solid-state transformers (SSTs). Such SSTs are required, for example, in future AI data centres, where power consumption per computer rack increases to levels of several hundred kilowatts or even
-
100%, Zurich, fixed-term The upcoming Molecular Engineering Thermodynamics (MET) Group at ETH Zürich is looking for a doctoral student to develop and improve computational tools for the molecular
-
CAD packages (Autodesk Revit, Archicad and cadwork3d) and work in a multi-disciplinary team of software engineers, architects, computer scientists Your projects will include multi-disciplinary
-
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