226 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:" positions in Switzerland
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
journey, from the collection and management of data to machine learning, AI, and industrialization. With a large multidisciplinary team of professionals across three locations (Lausanne, Zurich, Villigen
-
applying machine learning to PNT (Positioning, Navigation, and Timing) and geomonitoring challenges, including signal characterization and anomaly detection. Project background We are looking for a highly
-
& 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
-
(multi-view RGB imaging), drones, handheld and manual devices Contribute to the design and/or establishment of a phenotyping robot that can acquire data from RGB cameras and potentially other sensors
-
) Contribute to the strategic direction of research Publish high-impact research in leading journals and present findings at international conferences on energy systems and machine learning Collaborate with
-
devices Contribution to the design and/or establishment of a phenotyping robot that can acquire data from RGB cameras and potentially other sensors Improving phenotyping workflows and models to extract
-
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
-
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
-
. • Familiarity with machine learning, dimensionality reduction, clustering, and statistical modeling. • Strong communication skills, interest in interdisciplinary work, and ability to train students and postdocs.
-
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