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–control study with collection of wearable data and hormone profiles in healthy individuals and patients Integration of physiological data from wearable devices (e.g., activity, heart rate, temperature) with
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and hardware security assurance for embedded systems by combining advanced side-channel analysis, fault-injection techniques, AI- and machine-learning-assisted analysis, robustness evaluation, and
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computational image analysis, computer vision and machine learning. The aim is to develop robust and standardized methods to link structural, mechanical and biological properties to biomaterial performance and
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assurance for embedded systems by combining advanced side-channel analysis, fault-injection techniques, AI- and machine-learning-assisted analysis, robustness evaluation, and quantitative security assessment
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for analysing authentic, synthetic, and manipulated images or videos. The work will combine predictive performance with explainability, uncertainty estimation, robustness, and generalization. Attention will be
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30th September 2026 Languages English English English Build AI digital twins for real-time fermentation control and drive the future of biotech PhD scholarship within Bioprocess Engineering Apply
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learning. The aim is to develop robust and standardized methods to link structural, mechanical and biological properties to biomaterial performance and tissue reconstruction. The PhD candidate will work with
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methods, fine-tune and align them for specific operational domains, and deploy them locally under full control of sensitive operational data. A central maritime use case will be condition monitoring and
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associated tasks must be carried out in accordance with the applicable laws and regulations for government employees, including also the Act on Control of the Export of Strategic Goods, Services and Technology
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-minute market time units, automated mFRR energy activation, and flow-based market coupling further increase the need for decision-support methods that are fast, robust, risk-aware, and suitable for real