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research in the disciplines of Artificial Intelligence, Computational Biology, Databases, Graphics, Hardware / Architecture, Human-Computer Interaction, Operating Systems / Networking, Programming Systems
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processing systems, computer networks, and intelligent software-intensive systems. The Institute plays a strategic role in advancing data-driven and intelligent technologies that support emerging digital
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(preferred). 5+ years of experience in systems integration across hardware, software, and networked environments, preferably in healthcare IT, cybersecurity frameworks, or critical infrastructure. Expertise in
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to, Networks and Systems, Internet of Things (IoT), Embedded and Cyber-Physical Systems, Systems-on-Chip, Computer Systems and Architecture, Networking and Communications, Hardware/Software Co-Design and Systems
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. ________________________________________ Requirements • Masters or PhD in a field related to Sociology, Psychology, Human Geography, Geospatial Science, Environmental Science, Architecture, Landscape Architecture, Public Policy • Experience with
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on experience in the A/E/C industry. Work within the software platforms within U Facilities to support project teams and members with project assistance in the office and on job sites. • Perform architectural BIM
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surface patterns. This will support the study of artists’ techniques, enable enhanced visualization, and facilitate change monitoring over time. The project will also develop a visualization architecture
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. Carry out the implementation of back-end and APIs. Manage the software life cycle. Perform container hardening, pentesting. Where to apply Website https://seuelectronica.upc.edu/en/procedures/call-for
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17 Jan 2026 Job Information Organisation/Company Tallinn University of Technology Research Field Architecture » Other Computer science » Other Engineering » Civil engineering Geography » Human
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learning procedure such as the one included in the ArcaNN1 software that was developed in our laboratory. This project will merge an architecture that focused on ML/MM for spectroscopy2 to ArcaNN, aiming