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Scene Understanding Detection and Identification of Objects (SSUDIO) project. The purpose of this project is to develop scene understanding from 3D scans of ships by applying machine learning/computer
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breast cancer dormancy -Participate in the development of novel biomaterials to model in vitro breast cancer micro-units in controlled 2D and 3D microenvironments -Monitoring breast cancer cell dynamics
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, numerical methods, and Earth system modeling to develop and evaluate a coupled xylem–phloem transport framework that translates multiscale physics into next-generation vegetation model schemes. Key
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qualifications include (but are not limited to): Sophomore or Junior level Software development experience Microcontroller knowledge (i.e. Arduinos, Raspberry Pis, etc.) 3D modeling experience and knowledge of 3D
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natural fibers. 2.Design of 3D printing mixture. 3.Chemical treatment and pre-soaking RCA particles in an acid. 4. Deep learning modeling of parameters of cement composites. 5. Preparation of reports and
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: Turbulence and VCA induced vortex modelling as safety cases for Urban Air Mobility Supervisor: Prof. Dr. rer. nat. Matthias Mauder, Chair of Meteorology and co-supervised by at least one
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-ion batteries. Application of novel types of battery materials will affect current distribution in the cell. The project aims to model ionic and electronic transport in the battery cell based on 3D
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geometries. Current simulation-based approaches require complex 3D meshes and are often too slow for practical medical use. This project aims to create accurate and rapid surrogate models by combining physics
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part of PPPL's international collaboration with CEA, France. The final goal will be modeling self consistently plasma and impurity transport in the edge of a magnetic fusion device, tokamaks and
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(WP4), led by IEM, focuses on the design, modeling, and optimization of a laboratory-scale EC-MF pilot using promising electrocatalytic materials synthesized in WP1.3. The postdoctoral researcher will