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Field
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) position on the development and application of phase field methods for dynamic earthquake rupture simulations in the context of enhanced geothermal systems, CO2 sequestration, and earthquake physics
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 11 days ago
following conditions: Scientific area: Industrial Engineering and Management Work plan: Research in Last Mile (routing models, simulation, and Artificial Intelligence). 1. Duration and Terms: Duration of 12
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morphology from URA and greenery inventories from NParks—to support neighbourhood-scale simulations using the Open Foam and urbanMicroclimateFoam CFD models. These simulations evaluate how urban form
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develop and refine mathematical models of microbial interactions capable of predicting dynamics of engineered communities, and implement computational simulation, design, and inference frameworks
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Stimulation, Computational Modelling, Biomedical Engineering and Biophysics, Neurosciences Admission requirements: Bachelor’s degree in Biomedical Engineering and Biophysics. Must have attended courses
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training deep learning models on biological, chemical or related datasets Proficiency in Python for data science and machine learning Possess sufficient breadth or depth of specialist knowledge with deep
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higher education institution in conjunction with an R&D unit in Chemistry, Biochemistry or related fields. Knowledge of protein modeling, virtual screening and classical molecular dynamics. In case
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computational methods for automatically creating extremely large simulation models faster and better, including mesh generation and boundary condition application. The posts are primarily office based, with some
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: Essential criteria PhD in bioinformatics, computational biology, or a related discipline Extensive experience and expertise in applying/developing and training deep learning models on biological, chemical or
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highly skilled Postdoctoral Fellow with a proven dual‑mode research profile capable of independently performing laboratory experiments and coding predictive AI models in Python to forecast biomaterial