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decision is made Strong background in computational modeling and numerical methods Experience with multiphase flow modeling (e.g., TFM, CFD-DEM, DNS, LBM) Solid programming skills Experience working in Linux
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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
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Infrastructure? No Offer Description Work group: IAS-9 - Materials Data Science and Informatics Area of research: PHD Thesis Job description: Your Job: Digital methods for inverse materials design are essential
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conduct researches of transport phenomena and dynamics of chemical reaction using the approaches of active matter, nonequilibrium statistical physics, theory/mathematical calculation method of nonlinear
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on developing new methods and applications of metabolite profiling using a combination of mass spectrometry (MS) and NMR platforms which provide a broad-based approach for biomarker discovery and systems biology
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until the grant's contract is done; proven previous experience with articles published in first quartile journals (Q1) on the Discontinuous Galerkin Finite Element Method (DGFEM); experience implementing
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subsequent PhD degree in (astro-)physics, computer science, engineering, or other related fields, with a strong focus on numerical simulations Experience in the development of numerical methods for multi
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— The score obtained in the curricular evaluation method is expressed on a numeric scale of 0 to 20, considering the valuation up to two decimal places. 6.3 — The jury deliberates by vote justified according
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achievements in the area of biomedical engineering, in particular: designing computer-aided diagnosis systems; analyzing images, signals, and multimodal data, particularly using artificial intelligence methods
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through measurements in an acoustic tank on plate and cylinder models. - Development of analytical and numerical methods to describe the coupling of vibroacoustics in heavy fluids and thin structures