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Field
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chem- and bioinformatics to computer vision and social network analysis. Machine learning with graphs aims at exploiting the potential of the growing amount of structured data in all these areas
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research focuses on the development of new methods and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains from chem- and bioinformatics to computer vision and
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that will consider the electromagnetic aspects, through computer modelling and simulation, and then identify material systems that enable the design and manufacture of antennas for test and characterisation
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written and spoken. Experience with experimental fluid mechanics and computer vision is an advantage. Our offer We offer a stimulating, multidisciplinary research environment within the ETH Domain, with
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external organisations. Applicants from a range of disciplines or fields will be considered, including electrical, electronics, computer systems or telecommunications engineering. If you're curious about
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generation of social, computer-based, and cyber-physical systems that make a substantial contribution to the welfare of our society, for example, via embodied intelligent systems that are tailored to users
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Machine Learning for Image Classification. Eligibility You must: We would like you to have: sound knowledge of machine learning, computer vision and image processing strong programming skills. How to apply
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is offering multiple studentships for candidates from backgrounds spanning the physical and computer sciences. These students will develop core expertise in robotic, digital, chemical and physical
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: MSc in Physics, Materials Science, Nanoscience, Computer Engineering, Data Science, Gaming Engineering or a related discipline. · Knowledge: Strong coding skills in Python and knowledge in materials
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qualified women. About the position The position contains both teaching duties and participation in research projects. The research project topics focus on improving object recognition through computer vision