209 engineering-"https:"-"https:"-"https:"-"Data-driven-Materials-Modeling" positions at ETH Zurich
Sort by
Refine Your Search
-
100%, Zurich, fixed-term We are seeking a skilled infrastructure engineer to join the Apertus team. The ideal candidate will own the container image stack behind our pre-training, post-training, and
-
10%-30%, Zurich, fixed-term The Chair of Energy Systems Analysis (ESA), within the Department of Mechanical and Process Engineering (D-MAVT) at ETH Zurich, is looking for a Student Assistant to
-
Setting up laser system for laser cooling, trapping, and imaging of rubidium-85 atoms Engineering and assembling UHV (ultra-high vacuum) system with excellent optical access for the quantum processor
-
100%, Zurich, fixed-term We are seeking a skilled engineer to join the Apertus evaluation effort. The ideal candidate will build and operate the evaluation codebase and pipelines that inform our
-
. This groundbreaking technology relies on the development of state-of-the-art X-ray optics enabled by cutting-edge micro- and nanofabrication techniques. To support this effort, we are seeking a highly motivated
-
100%, Zurich, fixed-term At the Center for AI Value, part of the Technology Marketing Group at ETH Zurich, we investigate how organisations can turn generative and multimodal AI into measurable
-
100%, Zurich, fixed-term We are seeking a skilled engineer to own the technical release path of Apertus models. The ideal candidate will integrate Apertus into the open-source inference ecosystem
-
100%, Zurich, fixed-term The Optical Materials Engineering Laboratory (Prof. David J. Norris) in the Department of Mechanical and Process Engineering (D-MAVT) at ETH Zurich investigates
-
, PCBs) Note: This is not a position in biomedical engineering and there is no health focus. Project background Wearable EMG provides a direct and unobtrusive way to sense muscle activity underlying hand
-
100%, Zurich, fixed-term We are seeking a skilled engineer to join the Apertus post-training effort. The ideal candidate will develop, run, and evaluate the SFT and reinforcement learning pipelines