179 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" positions at ETH Zurich in Switzerland
Sort by
Refine Your Search
-
of machine learning, AI, and cancer genomics. Our lab develops novel machine learning methods to understand biological systems and cancer, with a strong focus on genomics and translational impact. We work in
-
the environmental drivers that regulate these processes. We will use machine learning approaches (XGBoost, SHAP analyses) for the flux partitioning, complemented by existing tree dendrometer and sap flow measurements
-
experience working in collaboration with biological or clinical labs and with groups with a strong machine learning background. The starting date is by mutual agreement. We expect a pronounced interest in
-
thinking with a structured, quality-focused approach to data and methods. Ideally, experience in one or more of the following: data engineering, building data-driven apps, computational linguistics, machine
-
of machine learning and high-performance computing, tackling complex, open-ended challenges to deliver scalable solutions. You will design and optimize a software-defined infrastructure that enables cutting
-
COMPAS XR framework developed at ETH Zürich. Project background The successful candidate will work at the intersection of computational design, XR, human-computer interaction, and robotic fabrication, with
-
forces and stress fields in such systems Develop and use machine-learning based models to correlate particle deformation and contact forces in 3D systems Profile Applicants for this PhD position
-
contributes to positive change in society You can expect numerous benefits , such as public transport season tickets and car sharing, a wide range of sports offered by the ASVZ , childcare and attractive
-
benefits , such as public transport season tickets and car sharing, a wide range of sports offered by the ASVZ , childcare and attractive pension benefits chevron_right Working, teaching and research at ETH
-
. The combination of biological and technological aspects is central in our group and in this project. A possible candidate should have strong disposition to learn and improve novel methods, should be very open to