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Field
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broad spectrum of fields, from core to applied computer sciences. Its vast scope also benefits our undergraduate and graduate programmes, and we now teach courses in several engineering programmes
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in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment focuses on methodological development in cryo
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, incorporating their own ideas and experience in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment focuses
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your application: A doctoral degree in automatic control, electrical engineering, computational materials science or related. Research experience in battery tests, machine learning, data-driven
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year. You should have knowledge and experience in bridging quantum and classical machine learning, and be fluent in English, both written and spoken. Assesment criteria Qualifications that are considered
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conduct research on the theoretical foundations of mathematical optimization, as well as its applications to emerging challenges in machine learning and engineering. You will write and submit research
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tasks that require coordinated base-arm-hand behaviors in dynamic environments. We seek candidates with a strong background in robotics and machine learning, and demonstrated experience in at least two of
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a Postdoc you are given/provided an opportunity to develop your independence as a researcher with the support of senior colleagues. The appointment is limited to 3 years and is full time in accordance
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some pedagogical training. In addition to research, the position includes teaching, supervision, and other teaching-related tasks amounting to 20% of the working time. What we offer As a Postdoc you are
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theory, and learning theory to design efficient and robust decentralized AI systems. As postdoc, you will principally carry out research. A certain amount of teaching may be part of your duties, up to a