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: Investigation of precipitation and crystallization processes in phosphorus recovery using experimental and numerical methods Supervisor: Prof. Sergiy Antonyuk C2: Experimental investigation and modeling
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Your Job: We are looking for a PhD student to contribute to the development of fast, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular
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: Perform high-fidelity thermal and mechanical numerical simulations for metal additive manufacturing. Develop and implement PIML models for analysis and optimization of metal additive manufacturing
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for the captioned post. Duties and Responsibilities Conduct advanced research in structural health monitoring, including hardware development. Perform numerical studies and model testing. Analyze and interpret data
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to shape a desired area of focus within the applied climatology framework. Successful candidates will be involved in field sampling, numerical/statistical modeling of hazards/impacts, and outreach to local
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to assess the realism of IPSL climate model regarding air-sea carbon exchanges - Application of these diagnostics to a set of numerical simulations to quantify improvements in C-cycle in the new IPSL climate
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concrete model problems and numerical examples to guide and prototype the development Qualifications and personal qualities Applicants must hold a master's degree or equivalent education in applied and
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, modeling and Remote-sensing to Transform carbon budgets, CLARiTy’ (https://www.schmidtsciences.org/vicc/) will reduce the persistently high land flux uncertainties in GCB by an order of magnitude. To achieve
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numerical modelling tools (e.g., Delft3D, HEC-HMS, MIKE, GR4J) is advantageous. Strong analytical and visualization skills with excellent scientific writing and communication abilities. Ability to work
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attention to phenomena dependent on strain rate, temperature, thermal history, and microstructure; elasto-viscoplastic and micromechanical constitutive modeling, developed in academic and/or industrial