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this mysterious transition. The current project aims to date the oldest ice in Antarctica using a combination of numerical modeling and geophysical observations. It will focus on two complementary ice archives
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Computationally efficient modelling & simulation and applications School of Electrical and Electronic Engineering PhD Research Project Self Funded Dr Lingzhong Guo Application Deadline: Applications
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challenging conditions, and in modelling coastal processes such as coastal erosion, rip currents, and coastal flooding. You will have experience in coastal processes and numerical modelling. Your principal role
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, Berlin 10099, Germany [map ] Subject Areas: Numeric Analysis, Partial Differential Equations Appl Deadline: 2026/04/11 04:59 AM UnitedKingdomTime (posted 2026/02/13 05:00 AM UnitedKingdomTime) Position
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ALMA MATER STUDIORUM - UNIVERSITA' DI BOLOGNA - - DIPARTIMENTO DI INGEGNERIA CIVILE, CHIMICA, AMBIENTALE E DEI MATERIALI | Italy | 20 days ago
. Structural optimization and numerical modeling. Where to apply Website http://www.unibo.it Requirements Additional Information Eligibility criteria to apply for research grants fill out the form available
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, Mathematical Modeling, Operations Research, Data Science, Numerical Computing, etc; l Preferably under 35 years old. n Assistant Professor l Ph.D. in Mathematics; l Promising research trajectory and a well
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machine learning techniques for building efficient reduced-order models in the context of the numerical simulation of parameterized partial differential equations. The analysis of recent deep learning
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methods scale as O(Nd), where N is the number of degrees of freedom per dimension d. Foundational kinetic models often have N∼256 and d≥6, making direct numerical simulation intractable with traditional
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engineering or related fields. Strong background in fluid mechanics, scientific computing, numerical methods, PDEs, and/or data-driven modeling Interest in interdisciplinary research and open science
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complementary data from other Mars missions to strengthen current models and provide comparative insights that enhance research conclusions from Hope observations. Develop Machine Learning methods and run