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. The PhD candidates will focus on developing methods that utilize remote sensing and AI supporting precision forestry. Remotely sensed data, such as images, lidar, and photogrammetric point clouds acquired
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, high-dimensional imaging, and clinical covariates. Apply these methods to spatial transcriptomics and fluorescence imaging data to gain a more precise understanding of complex biological systems
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build a closed-loop, verifiable self-healing prototype for cloud-native 5G/6G operations, evaluate it under realistic degradations (failures/underperformance), and produce results that matter for both
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combination of in vivo voltage imaging, behavior, opto- and chemogenetic manipulation, and ex vivo patch-clamp electrophysiology. The candidate will train mice in various decision-making tasks and record
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inducing oscillation or cascading secondary failures. The research focus is hands-on and systems-oriented: the candidate will build a closed-loop, verifiable self-healing prototype for cloud-native 5G/6G
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spatial memories and how these processes are influenced by addictive substances. You will use state-of-the-art in vivo two-photon imaging and electrophysiology to record neuronal activity in rodents
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-economic growth paradigm and including its ever-increasing demand for electricity. In addition, comprehensive future large-scale landscape changes can be anticipated due to a broad range of needs and
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and experiments and documentation of research activities of the of SAFE center. The position as researcher will cover research, dataset development, prototype deployment, and collaboration with
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experience in biomedical applications such as biosensing, diagnostics, imaging and/or drug delivery Personal characteristics To complete a doctoral degree (PhD), it is important that you are able
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Analysis: Experience with programming (for example Python/Matlab) and image analysis is highly emphasized. Such experience should be documented. Scientific Curiosity: You are eager to bridge the gap between