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mediated synthesis in the cortex of a healthy adrenal gland and implementing them into numerical simulation codes for handling complicated spatial profiles. Validating the models by comparing
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description of steroid enzyme mediated synthesis in the cortex of a healthy adrenal gland and implementing them into numerical simulation codes for handling complicated spatial profiles. Validating the models
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of Artificial intelligence, Machine learning, Numerical simulation, Formal verification. Such methods include, among the others: AI-guided simulation of the mathematical models of the patho-physiology and PK/PD
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health in Europe. This project is part of Work Package 3 (Trustworthy Data and Models) of the EU Horizon ENDOTRAIN doctoral training network. The recipient of this PhD position will carry out research
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models, and obtain numerical solutions for the research topics as agreed, and described above Preparation of scientific papers Dissemination of results in project meetings, and national and international
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education until obtaining a PhD degree Develop mathematical models, and obtain numerical solutions for the research topics as agreed, and described above Preparation of scientific papers Dissemination
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partners: SINTEF Energi, NTNU, KTH The project aims to advance knowledge on clamping force evolution through experimental studies, sensor-based monitoring, and numerical modelling, laying the foundation
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in high-impact factor SCI journals Extensive material characterization experience (XRD, SEM, FTIR, Mercury Intrusion Porosimetry (MIP)) Experience with numerical modelling (e.g., COMSOL/ANSYS
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-mechanical ( THM) model considering the climatic conditions to investigate feasibility and efficiency of the EG technology; (iii) (3) Develop THM numerical model to investigate the road damage mitigation
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for the position. Preferred selection criteria Bachelor’s degree in civil engineering Experience in analytical methods and numerical modelling Proficiency in at least one programming language, e.g. C++, Python