224 assistant-professor-computer-science-"https:"-"https:"-"https:"-"https:"-"UCL" positions at ETH Zurich
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physics simulation, rendering, and neural graphics. Profile Bachelor’s, Master’s, or PhD in Computer Science, Computer Graphics, or a related field. Strong proficiency in C++ and Python, with a track record
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Sciences with strong IT/programming skills, or in Computer Science/Physics with interest in geoscience and sensors, to support sensor-noise analysis, calibration workflows, and seismic-coverage modelling
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networks Publish results in peer-reviewed journals and present at scientific conferences Co-supervise MSc, BSc, and PhD students and contribute to teaching in the Forest and Landscape Management program
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assurance Evaluate and help introduce new automation technologies and methods within the core facility Profile PhD in life sciences, biotechnology, bioengineering, or a related field Strong background in
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is carried out by the responsible recruiters and not by artificial intelligence. ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our
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experience and interests in the letter alligned to the job and in a wider context. The goal of your letter of motivation should be to help us gauge your interest and motivation in pursuing this research
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agreement. We develop computational methods to accelerate materials discovery through defect engineering, with a focus on extreme environments. Application areas include fusion reactors, hydrogen systems, and
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atmospheric/environmental sciences, physics, computational science, engineering or a related field A background in numerical modelling, statistical data analysis and/or programming skills is highly encouraged
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the power of both classical and quantum computing resources? How can we exploit or take inspiration from quantum physics to develop cutting-edge machine learning? Your work will encompass a diverse array of
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, ACHIEVE consortium The primary focus of this role is to serve as the Knowledge and Technology Transfer (KTT) Expert within the ACHIEVE consortium as part of the SWEET funding programme of the Swiss Federal