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the resilience of offshore marine infrastructures exposed to harsh and extreme environmental conditions. Through this PhD scholarship, you will contribute to the development of a physics-informed and data-driven
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on damage modelling. Calculation of linear and nonlinear response of offshore structures exposed to various loading scenarios including operational and extreme environmental conditions Development of accurate
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Josip Juraj Strossmayer University in Osijek School of Applied Mathematics and Informatics | Croatia | 3 days ago
field of mathematics, for work on the project Croatian Science Foundation „Scaling in stochastic models“ (Project ID: DOK-2025-02-9144), according to the tender Croatian Science Foundation „Razvoj
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relation to local environmental cues such as light intensity, wind conditions, and visual structure. A key focus will be on how Dipteran insects perceive and use these cues—especially visual landmarks and
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Description Water can move in two interconnected realms: the fast, visible rivers at the surface and the slower, pressure-driven flow within substrates. Today, engineers can model each realm
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excursions. The PhD student will work on analysing the reliability of paleomagnetic records, deriving uncertainty estimates, and building time-dependent models of the paleomagnetic field evolution using a
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). Have a background as a health professional or consumer advocate who has worked with (or conducted research with people with health conditions. Additionally, it is preferred if you have: experience/study
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apply a fast and efficient forest trait mapping and monitoring method based on the Invertible Forest Reflectance Model. A machine learning / deep learning framework will be explored and developed
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available sensor and meter infrastructure, affordable computational resources, and advanced modeling algorithms. MPCs excel in handling constrained optimizations and new operational conditions, whereas RLs
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the eligibility of PIML / PINN models in both open and closed-loop contexts; - Derive the necessary conditions for that eligibility (data to collect, model architectures, training procedures, …); - Implement PIML