Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
. Empa is a research institution of the ETH Domain. The Laboratory for Building Energy Materials and Components develops advanced and/or low eco-impact, porous materials for insulation, sorption, and
-
) develops advanced optical technologies, including imaging, spectroscopy, and laser ablation methods. Our goal is to bridge these cutting-edge laser technologies with clinical practice, developing solutions
-
Engineering Lab . Job description Collaborate with other researchers to develop high-fidelity emulators for large-scale, energy system optimization models Lead the design and implementation of innovative
-
basic and clinical scientists to advance our understanding of health and disease and to develop pioneering therapies benefiting the lives of patients in areas of unmet need. With more than 70 research
-
optimization and LLM alignment: design preference-based training and fine-tuning methods (RLHF, PPO, DPO, reward modeling) for medical and multilingual LLMs. Agentic and tool-augmented AI systems: develop
-
of catalysts, electrodes, and ionomer membranes with high time resolution, operando x-ray measurements. Develop electrode architecture and catalyst/electrode modification strategies for enhanced durability
-
polymer additive chemistry. A more recent focus of the group is the development of sustainable polymer and additives. To strengthen activities in this area, we investigate development of functional covalent
-
of electronic devices has a long and successful history of accompanying experimental developments, be it for transistors or memory cells. Nowadays, to be of practical relevance, such technology computer aided
-
The Institute of Molecular Systems Biology (IMSB) at ETH Zurich invites applications for a Postdoctoral Researcher in Metabolomics & Technology Development in the laboratory of Prof. Dr. Nicola Zamboni. Project
-
" (D2M). This innovative project is a collaboration between the University of Basel, the Bern University of the Arts, and the FHNW. The goal is to develop a highly automated, reproducible pipeline