33 coding-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" "U.S" "U.S" positions at ETH Zurich in Switzerland
Sort by
Refine Your Search
-
(FOPH) of Switzerland and the Centers for Disease Control and Prevention (CDC) of the United States. We value good software engineering practices. We perform code reviews, have automated testing pipelines
-
code, projects, etc) Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered. For further
-
of research excellence through peer-reviewed publications Evidence of comittment to reproducibity in bioinformatics through the use of Code Repositories Evidence of ability and experience in handling
-
related field Solid background in physical optics, experience in interferometry and/or cryogenic optics is an asset Extensive experience with optical design and simulation tools (e.g. Zemax, Code V, FRED
-
quantitative skills and comfort with coding, and good analytical thinking You are committed to working in an interdisciplinary team blending climate modeling, geochemical process models, and new geochemical data
-
) 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
-
mechatronics systems is a plus Excellent coding skills in python, ROS, and RL&IL pipeline experience on simulator and training libraries. Knowledge on C++ is a plus Experience with Physics simulators such as
-
programming skills (ideally Python) and commitment to clear, reproducible, well-structured code Working knowledge of SQL and/or NoSQL databases (and motivation to deepen your expertise) Strong analytical
-
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
-
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