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-class or 2:1 (or international equivalent) Master’s degree in Computer Science, Robotics, Mechatronics or Electronic/Electrical Engineering, or a related field. • Knowledge of machine learning/deep
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funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The NETCOM group is recruiting
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academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and
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system stems from the need to increase efficiency in marine monitoring. Furthermore, existing computer vision solutions often depend on cloud computing infrastructure and require specialized expertise. A
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). The Computer Science group is looking for students to work on one of the following projects Distributed Intelligence for Self-Organising Cloud–Edge Infrastructures Carbon-Conscious Resource Scheduling for AI Workloads
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the EU Research Framework Programme? Not funded by a EU programme Reference Number 165143 Is the Job related to staff position within a Research Infrastructure? No Offer Description Automation
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engineering, or atmospheric science* Expertise in and passion for computational modelling and software development/engineering Expertise in cloud physics or contrails preferred but not required Creative problem
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, modeling, or AI/ML approaches in agricultural or environmental research. -Proficiency in server administration, distributed computing, and cloud platforms (AWS, Azure, Google Cloud). -Knowledge of full-stack
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Offer Starting Date 20 Jan 2025 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer
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, or closely related topics. Interest in data analysis and computational modelling. Interest in software (cloud platforms/data visualization) and related applications to integrate real-world energy data. Very