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for the development of more predictive preclinical platforms. This PhD project is part of the ANR JCJC EXOFLEX project, which aims to develop an instrumented microfluidic platform capable of simultaneously controlling
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for transformers, map the benefits and risks of increasing the load and temperature limits, and pilot new concepts for risk control. The PhD Position belongs to Work Package 1 of KSP UPLOAD: ‘System-level Benefits
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will also be integrated into the wider CENSEMAT research environment at Aarhus University, allowing computed models and predictions to be tested directly against advanced experimental characterisation
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designed to prevent excessive mucus degradation. Finally, we will develop a model to predict disruption of the gut mucosal barrier. This model will be evaluated in non-invasive samples from individuals with
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Research Network – Krakow Institute of Technology Position: PhD Student – Scholarship Holder in the FIRST TEAM FENG Project Łukasiewicz Research Network – Krakow Institute of Technology announces an open
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production.The PhD position in The SySi Team will focus on the integrated steam system design and control in a multi-energy vector context, using physics-based non-linear Model Predictive Control (MPC
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efficient navigation algorithms for multirotor operations around vessels. The role will focus on integrating drone airspace-usage predictions with Vessel Protected Volume models, developing optimisation and
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regularly in its various training and research activities, as well as the weekly seminars in IDAEA-CSIC. Where to apply Website https://www.idaea.csic.es/job-offer/phd-position-understanding-and-predicting-n
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processes. The excellent outcrop exposure due to limited vegetation cover, and extensive mineral occurrences provide a unique natural laboratory to advance predictive mineral system models. Our research will
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heterogeneous digital health systems and for developing predictive models. D3. Controlling the financial costs associated with the use of agentic AI