229 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "The Institute for Data" uni jobs in Switzerland
Sort by
Refine Your Search
-
Listed
-
Employer
- ETH Zurich
- Nature Careers
- University of Basel
- ETH Zürich
- Empa
- HES-SO Genève
- CERN
- EPFL - Ecole Polytechnique Fédérale de Lausanne
- Graduate Institute of International and Development Studies, Geneva;
- Paul Scherrer Institut Villigen
- School of Architecture, Civil and Environmental Engineering ENAC, EPFL
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL
- 2 more »
- « less
-
Field
-
Center for Project-Based Learning. The successful candidate will contribute to research at the intersection of embedded machine learning, signal processing, and smart sensing systems, with applications in
-
programming skills in Python Experience with machine learning systems or LLM-based architectures Experience working with complex data systems or developing applied AI prototypes Familiarity with modern AI tools
-
80%-100%, Zurich, fixed-term We are looking for a Research Engineer to join ongoing and future research projects at the intersection of machine learning, and structural design (e.g. trusses, space
-
methods and approaches are needed to better tackle the challenges posed by increased uncertainty and complexity. Machine learning (ML) and artificial intelligence (AI) methods have shown promise
-
& Machine Learning: Experience in deploying machine learning models and data science workflows in a research context (e.g., cheminformatics, predictive modelling). Design of Experiments (DoE): Knowledge
-
-read sequencing data analysis is highly desirable. Familiarity with signal processing or applied machine learning is advantageous. You should demonstrate strong motivation to develop innovative
-
dynamical systems, and machine learning, with applications to synthetic biology and biomolecular circuit design. Our research develops mathematical and computational frameworks for understanding and
-
Systems.”Funded through an ETH Zurich Career Seed Award, this project aims to develop scientific machine learning frameworks that integrate physics-based modeling with neural network architectures. The goal
-
of cutting-edge tools, models, and strategies to understand and engineer immune systems for translational medicine. Candidates may use integrative approaches that combine immunogenomics, machine learning
-
. • Familiarity with machine learning, dimensionality reduction, clustering, and statistical modeling. • Strong communication skills, interest in interdisciplinary work, and ability to train students and postdocs.