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Field
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learning methods. Develop deep learning architectures (e.g., variational autoencoders, graph neural networks, transformers) for cross-omics data representation and feature extraction. Apply multi-view
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and experimentation in the area of Multi-agent Agentic AI systems applied to 6G network and service management. By leveraging recent advances in Large Language Models (LLM) and other key agentic tools
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into public security, focusing on sociotechnical reconfigurations and their political, regulatory, and social impacts. With an interdisciplinary approach (Critical Security Studies, STS, and Surveillance
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modeling and networked biological systems. You will work at the intersection of high-performance computing (HPC), computational biophysics, and machine learning, leveraging leadership-class computing
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as evidenced by earlier research publications; Creation of virtualised container-based testbeds for experimental research on network security, integration of industrial use cases and digital twins, AI
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security. We utilize our expertise in numerical discretization techniques, high performance computing, mesh generation, and geometry representation for a wide variety of physics applications. Our intention
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to democratic stability in times of crisis. Against the backdrop of multiple crises and the changing security landscape, the project examines the social conditions under which democracies in the Baltic Sea region
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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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of these reusable packaging using IoT sensors and deep learning techniques embedded in the sensors. During the preliminary work, neural network models were developed to perform simple tasks using accelerometer data
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Requisition Id 16262 Overview: We are seeking a postdoctoral researcher to work at the intersection of tensor networks, quantum algorithms, scientific computing, topological physics, and quantum