182 computer-programmer-"https:"-"CEA-Saclay" "https:" "https:" "https:" "https:" "https:" "Dr" "UCL" positions at ETH Zurich
Sort by
Refine Your Search
-
, we plan to study atmosphere/ocean interactions at multiple spatial resolutions, and investigate consequences for tropical cyclones, clouds and precipitation and how they depend on spatial resolution
-
The Institute of Molecular Systems Biology at ETH Zurich is inviting applications for a Full Stack Web Developer for Life Science Research in the laboratory of Prof. Pedro Beltrao . The Beltrao
-
-phonon coupling elements. With these, dedicated scattering rates can be computed and then used in quantum transport simulations. Down the line, we aim to pre-train a common GNN backbone model capable
-
100%, Basel, fixed-term The Computational Biology (CoBi) group, led by Prof. Dagmar Iber, develops data-driven, mechanistic models of biological systems using advanced imaging and computational
-
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
-
using emerging non-invasive exhalomics (exhaled breath metabolomics) approach. The research program integrates animal experiments with advanced analytical techniques and bioinformatics to enhance
-
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
-
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
-
interest in data-intensive systems. You bring a solid foundation in software or data engineering, typically developed through a Master’s degree or higher (e.g. PhD) in Computer Science or a related field, or
-
. Neuromorphic computing and ML deployment on digital and neuromorphic processors TinyML and EdgeAI and ultra-low-power inference for resource-constrained systems Techniques such as quantization, pruning