Sort by
Refine Your Search
-
are computationally expensive, making them clinically impractical at scale. The solution lies in image-based, data-driven (AI) models that learn to predict personalised fracture risk directly from routine bone-density
-
-learning models on resource-constrained hardware Candidates should also have experience or strong interest in Edge AI, TinyML, embedded machine learning, neuromorphic computing, or signal processing. We
-
Biology, Computer Graphics, Computer Vision, Control Systems, Deep Learning, Digital Humans, Earth Observation, Educational Technology, Efficient AI, Explainable AI, Haptics, Human-Computer Interaction
-
30%, Zurich, fixed-term The Professorship for Learning Sciences and Higher Education at ETH Zurich is seeking a motivated student assistant (30%) starting in October 2026. In this role, you will
-
processing, machine learning, and human-computer interaction. The goal of this PhD is to develop neuromotor interfaces for dexterous robot teleoperation using two sensing modalities: 1) surface
-
60%-80%, Zurich, fixed-term The Strategy & Analytics Group in the Unit for Teaching and Learning provides the evidence behind decisions about teaching at ETH Zurich. The team runs ETH-wide projects
-
methods involving molecular surface display and deep sequencing to study force-dependent behavior in protein systems. These datasets will, in turn, be used to train machine learning models capable
-
dynamics (MD) simulations including enhanced sampling techniques as well as machine learning. Profile Applicants should hold a M.Sc. in computational chemistry, chemistry, biochemistry, or physics
-
can significantly improve the treatment and outcome of oncological patients. Project background You will contribute to the design and implementation of machine-learning-based sparse 3D image
-
equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and