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-dimensional CFD simulations based on the Reynolds-Averaged Navier–Stokes (RANS) approach will be performed to model two-phase flow behavior and mixing within the CSTR. These simulations will be used to evaluate
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—governing the co-precipitation process. Leveraging the ASCC supercomputer at UM6P, three-dimensional CFD simulations based on the Reynolds-Averaged Navier–Stokes (RANS) approach will be performed to model two
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: Experience in salt or potash processing. Familiarity with process modeling and simulation tools. Experience with industrial or pilot-scale testing. Application Documents: Interested candidates should submit
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to work both independently and within a collaborative research environment. Preferred qualifications : Experience in salt or potash processing. Familiarity with process modeling and simulation tools
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morphing-wing UAV prototypes. Methodology: Design and Simulation: ABAQUS, SolidWorks, ANSYS, or COMSOL for topology optimization and aerodynamic modeling. Fabrication: Composite layup, 3D printing (FDM/SLA
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Computational Chemistry, Materials Science, or a related field. Strong background in computational chemistry techniques, including molecular dynamics, quantum mechanical simulations, and machine learning
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learning, imitation learning, and the integration of large language, vision–language, and vision–language–action models to improve generalization. A key objective is to design lightweight and efficient
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candidate will investigate robot learning methods for control and decision-making on edge robotic platforms. Research will focus on reinforcement learning, imitation learning, and the integration of large
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dynamics, quantum mechanical simulations, and machine learning. Proficiency in programming languages and computational software’s. Strong motivation and passion for research in the field of sustainable
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aerodynamic, vibration, and endurance testing campaigns. Assist in assembling and calibrating morphing-wing UAV prototypes. Methodology: Design and Simulation: ABAQUS, SolidWorks, ANSYS, or COMSOL for topology