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Field
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, computational biology, statistics or a closely related field. You have strong programming skills, preferably in Python, and experience with machine learning or deep learning. Experience in computer vision
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organizational theory, the learning sciences, digital transformation, digital technologies, human-computer interaction, and related fields. Within the specific field, the PhD student will engage in both research
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application! We are now looking for 1–2 PhD students for the Division of Computer Vision and Learning Systems at the Department of Electrical Engineering (ISY). Your work assignments Within the research unit
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skills, plus good presentation and writing skills in English, are required. Previous research experience in contributing to a collaborative interdisciplinary research environment is highly desirable but
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the findings at conferences and seminars. The PhD candidate will work within an interdisciplinary team bringing together psychologists, neuroscientists, specialists in movement science and computer scientists
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management of juvenile fish habitats, the student will be trained in a range of inter-disciplinary skills including coastal fish sampling, scientific diving, digital technologies and computer vision. Would
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, computer engineering, computer science, data science, mathematical engineering, robotics, or a closely related field. The candidate should have solid mathematical and analytical skills and a strong interest
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d'Azur. The team is composed of computer scientists but has a strong interdisciplinary focus, particularly in linguistics, philosophy, sociology, and law. MARIANNE proposes innovative methods for natural
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of offers available1Company/InstituteDepartment of Computer ScienceCountryAustriaCityInnsbruckPostal CodeA-6020StreetTechnikerstraße 21 a Contact City Innsbruck Street Technikerstraße 21 a Postal Code A-6020
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29 Aug 2026 Job Information Organisation/Company ARCNL Research Field Engineering » Computer engineering Engineering » Precision engineering Physics » Computational physics Physics » Metrology