25 coding-"https:" "https:" "https:" "https:" "https:" "Universitat de Barcelona" uni jobs at ETH Zurich
Sort by
Refine Your Search
-
. Joël Mesot. The closing date for applications is 22 February 2026. We are not accepting applications for this job through MathJobs.Org right now. Please apply at https://ethz.ch/en/the-eth-zurich/working
-
is 8 January 2026. We are not accepting applications for this job through AcademicJobsOnline.Org right now. Please apply at https://ethz.ch/en/the-eth-zurich/working-teaching-and-research/faculty
-
environment where philosophy meets data science, public health, medicine, and law? At the Health Ethics & Policy Lab (https://bioethics.ethz.ch ), you will join a team committed to shaping responsible
-
understanding of the aging of solid insulation under mixed-frequency medium-voltage stress, see https://doi.org/10.1088/1361-6463/acd55f for a relevant example research work of our team in this area. Profile
-
of predicting electronic, structural, and thermal quantities while leveraging underlying symmetries for computational efficiency. There will be a significant computational component in deploying multi-GPU codes
-
at https://ethz.ch/en/the-eth-zurich/working-teaching-and-research/faculty/faculty-affairs/ausgeschriebene-professuren/naturwissenschaften-und-mathematik/APTT_Anorg_Chem.html . Contact: faculty-recruiting
-
) Unsupervised machine learning and deep learning methods Analysis, visualization, and interpretation of learned design spaces Contributing to research outputs (prototypes, publications, open-source code) Profile
-
development, validation, and safe integration of locally hosted LLMs for automated coding of pediatric diagnoses from electronic health records (EHRs), with the goal of enhancing research capabilities and
-
disseminated through open-source code and scientific publications. Start: As soon as possible (applications reviewed on a rolling basis) Duration: 6 months (extendable) Job description Apply computational and
-
community Contribute to R data publication packages washr and fairenough Profile You care about data and code being concise and easily reusable You know how to use standard data science tools (Git, GitHub, R