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Field
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at scale raises privacy and real hardware constraint concerns. This PhD will focus on those challenges by developing a distributed, privacy-preserving NILM framework, so we can move from small research
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to develop and apply advanced remote-sensing approaches and AI-assisted image analysis to investigate the distribution, diversity, and spatial dynamics of Antarctic lichen communities, thereby contributing
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the Bavarian research network bayklif2 (https://bayklif2.de ) • PhD studies supported by our faculty's structured graduate program (RIGeL) • An outstanding scientific infrastructure, excellent international
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opportunity to be part of the BaySensAI project (https://go.ur.de/baysenseai ) and develop an AI-based prediction and monitoring system for biodiversity data as part of the Bavarian research network bayklif2
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, boosted by AI-data augmentation for extrapolating spectrum patterns from multiple sources. To design a scalable computing framework using a physics-informed neural network for distributed spectrum analysis
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for efficient and secure transmission of information in 5G/6G networks, using quantum communications technologies. Research and development of cloud-native approaches for Quantum Key Distribution (QKD
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, with both academia and industry recognising its importance. Distribution is an integral part of innumerous computer systems, providing them with essential improvements to aspects such as performance and
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optimization lab (EES EMPDO lab). The former focuses on intelligent energy network research, including: demand management and flexibility, digital twinning, data analytics, smart grid ICT architectures and
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, particularly in computer networks, operating systems, computer architecture and distributed systems Excellent programming, system building and measurement skills are required Be familiar with, and ideally worked
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Associate / PhD Student (m/f/x) within the MSCA Doctoral Network SLICE (due to funding, the salary is calculated according to MSCA regulation) starting October 1, 2026. The position is limited to 36 months