219 computer-science-intern "https:" "https:" "https:" "https:" "P" positions at ETH Zurich in Switzerland
Sort by
Refine Your Search
-
for the renewable energy sector via the M2A European Training Network (ETN), funded by the European Commission’s Horizon 2020 Marie Skłodowska-Curie programme. Project background M2A puts forward a robust methodology
-
80%-100%, Lugano, fixed-term The Swiss National Supercomputing Centre (CSCS) develops and operates a high-performance computing and data research infrastructure that supports world-class science in
-
researcher to advance our understanding of magmatic and volcanic systems. Job description Develop and lead an independent research program in magmatic petrology, volcanology, and/or geochronology. Publish
-
, with deep experience in appearance reconstruction and material modeling. Required Qualifications MSc in Computer Science or related field Strong background in computer vision and/or computer graphics
-
100%, Basel, fixed-term The Computational Biology (CoBi) group, led by Prof. Dagmar Iber, develops data-driven, mechanistic models of biological systems using advanced imaging and computational
-
datasets The position is limited to two years. Profile University degree (MSc or PhD) in data science, computer science, physics or a related field Experience in training and validating large-scale deep
-
Science at the ETH Zurich Institute of Environmental Engineering, with expertise in water chemistry assessments in forested ecosystems. The Silviculture group is part of the Chair of Forest Resources
-
Digital Twins for Human Learning. Project background In cognitive science, it is common practice to use cognitive models to understand human thought processes – including human learning. Large language
-
researchers across architecture, robotics, computer science, and engineering An engaged international community of researchers and educators Professional development and networking opportunities through
-
years. Profile University degree (MSc or PhD) in data science, computer science, physics or a related field Experience in training and validating large-scale deep-learning models on distributed systems