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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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Computer science » Informatics Researcher Profile First Stage Researcher (R1) Application Deadline 15 Sep 2026 - 21:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Hours Per
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geoscience and remote sensing methods with AI and advanced computing technologies for Earth observation (EO) applications, including climate science, forestry, or agriculture. Your doctoral research will
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About the Hubrecht Institute The Hubrecht Institute is a research institute focused on molecular and developmental biology. Because of the dynamic character of the research, the institute has a variable number of research groups, around 20, that do fundamental, multidisciplinary research on...
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INSTITUT CATALÀ DE NANOCIENCIA I NANOTECNOLOGIA | Universitat Autonoma De Barcelona, Cataluna | Spain | 3 months ago
ICN2 PhD Programme Programme description: The ICN2 offers a competitive PhD Programme to talented students who wish to develop a research career at one of the top European institutions in the field
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PhD Studentship: Efficient Long-Horizon Task Execution in Physical AI (deep learning, computer vision, robotics) Number of awards: 1 Award information: Fully funded PhD studentship covering Home
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ICN2 PhD Programme 2026 Programme description: The ICN2 offers a competitive PhD Programme to talented students who wish to develop a research career at one of the top European institutions in
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, a strong degree in computer science, cybersecurity, mathematics, or a related subject. Experience with cryptography, machine learning, or systems implementation is valuable, as are solid programming
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Deadline 15 Nov 2026 - 23:59 (Europe/Zurich) Country Switzerland Type of Contract Temporary Job Status Full-time Offer Starting Date 1 Apr 2027 Is the job funded through the EU Research Framework Programme
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for data-efficient vision foundation models. Foundation models in computer vision currently rely on massive datasets and brute-force scaling. This leads to high data requirements, hidden biases, limited