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with the PI and will mentor Master’s students and help guide PhD students. The offer is for one year full-time, renewable for a second year Research Focus Our work rethinks Internet architecture in light
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acceleration. We focus on energy-efficient circuit design and software-hardware co-optimization, with exciting applications in event-based vision. What we’re looking for: A PhD/Master in Electrical and Computer
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communication systems. A key part of this role is the design and development of simulation pipelines and digital twin architectures that couple virtual simulation environments with physical QKD security testbeds
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the end-to-end design and development of core system components, including AI-based encoding/decoding modules, model integration pipelines, and software architecture. Drive research and development
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Architecture, Ocean Engineering, Marine Engineering, Civil Engineering, or related field. Proficiency in hydrodynamic modeling tools (e.g., ANSYS AQWA or equivalent) and finite element analysis software (e.g
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Conduct applied research in AI, distributed computing, and software engineering under the direction of the project’s chief investigators. Develop and implement scalable and secure architectures
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; enrolled in a PhD program or a non-degree course. Experience in: a) ROS, programming in C++ and Python; b) Modelling and control. Work Plan: The work plan is divided into five phases: Phase 1 – Development
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of Information and Communication Technologies (ICT), namely Computer Science Engineering, and with experience in the development of rigorous software prototypes and projects related to blockchain, as
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Objective To design, implement, and validate a secure runner architecture based on the principles of isolation, ephemerality, and full encryption, using approaches such as hardware enclaves, infrastructure as
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architecture, including performance criteria and integration with existing telemetry and water management platforms; (d) implementing and training the selected models, incorporating expert validation to minimize