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Field
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coherence lifetimes for the solid state, and the ability to leverage the advanced nanofabrication methods of the semiconductor industry. The selected candidate will join the Quantum Hardware group lead by
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. The objective of this PhD project is to develop learning-based methods for maritime tracking and prediction in time- and safety-critical applications. Artificial intelligence techniques will be utilized in order
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issues in federated and decentralized learning systems. The aim is to develop novel methods for securing communication against passive and active adversaries, leveraging tools from statistical estimation
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to a senior position, design, organization of work, planning and conducting of experiments for VZ1, publication of scientific results, development and implementation of new innovative methods
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protocols to characterize both cellular and vascular properties of the TME. The approach will be validated using a combination of in silico models, computer simulations, and in vitro experiments using tumor
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tackling the above challenges with novel system designs and tailored AI/ML based methods. Candidate’s profile A First Class Bachelors degree and/or Masters degree in a relevant subject (computer
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addresses two intertwined goals: Improving Human Training: Developing adaptive haptic training strategies that help operators refine their skills through real-time skill estimation, multimodal feedback, and
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10 Dec 2025 Job Information Organisation/Company University of Siegen Research Field Computer science » Computer architecture Researcher Profile First Stage Researcher (R1) Positions PhD Positions
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) scientific studies Experience with relevant field data collection methods (e.g. chamber- or eddy covariance-based C flux measurements, biodiversity sampling methods) Computer programming skills (e.g. Matlab, R
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potential requires deeper insight into battery design, behavior, aging, safety, and efficiency. This PhD project develops advanced methods for battery pack design and optimization in electric powertrains