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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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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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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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computing, applied mathematics, computational physics, or another relevant discipline is required, Other requirements Required qualifications include strong skills in numerical method development
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mechanics, or advanced material behavior. Programming skills (e.g., Python, MATLAB, Julia,..), ideally with experience in numerical methods or scientific computing. Familiarity with machine learning
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have high relevance for industrial applications in many sectors. Research in solid mechanics at LTH is specifically focused on constitutive mechanics, numerical methods, microstructural mechanics
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) traditional numerical methods. Contract duration: The tasks described above will be carried out by the hired person as a short-term research project framed within the period between 01/02/2026 and 31/07/2026
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field strong analytical skills, with knowledge of fluid dynamics, aerodynamics, and numerical simulation methods basic programming skills (e.g., Python, MATLAB, or similar) and familiarity with data
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technology or system of higher education, in Portugal or abroad. 6.2 — The score obtained in the curricular evaluation method is expressed on a numeric scale of 0 to 20, considering the valuation up to two
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edge of energy systems and computational engineering, developing scalable methods to simulate and secure IBR-dominated grids. Your key responsibilities include: Conducting large-scale simulations