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Doctoral student in Materials Chemistry of Doped Organic Semiconductors in EU Training Network FADOS
to join the European Marie Sklodowska-Curie training network FADOS. The position is based in the research group of Christian Müller at the Department of Chemistry and Chemical Engineering. As part of
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, Electrical engineering, or equivalent. You will need strong written and verbal communication skills in English. Strong machine learning fundamentals (probability, statistics, optimization) and strong
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degree ( masterexamen ) of 120 credits or a Master’s degree ( magisterexamen ) of 60 credits* in Computer Science, Computer Engineering, Electrical Engineering, or a closely related field Strong written
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condensed matter physics, nanoscience, materials science, electrical engineering or a related field. You should have hands-on experience with microfabrication, nanofabrication or experimental device
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degree (or equivalent) in electrical engineering, electronics, materials science, nanotechnology, microelectronics, engineering physics or a related field -Experience of experimental laboratory work in
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your to-do list. The following requirements are mandatory: You hold a doctoral degree in a relevant field (applied mathematics, electrical engineering, transport engineering, industrial engineering
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, University Hospital Zurich, and the Swiss Epilepsy Clinic Lengg. PhD candidates will be enrolled in the Department of Information Technology and Electrical Engineering (D-ITET) at ETH Zurich
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, Biomedical Engineering, Robotics, Computer Science, Electrical Engineering, Neuroscience, Computational Psycholinguistics, Human-Centered Design, Industrial Design, Human Factors Engineering, or
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PhD position in Experimental Physics with focus on photonics and materials science (applied aspects)
, applied physics, optics/photonics, nanoscience, materials science, electrical engineering, or a closely related field. Fluency in English is mandatory. A documented background in photonics
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into soft and deformable thermal energy-harvesting devices. Characterization and optimization of the electrical, electrochemical, mechanical, and energy-conversion performance of materials and