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, ill-posed nonlinear inverse problems Numerical optimization techniques Machine learning Strong programming skills in Matlab and/or Python are required. These should be documented, for example through a
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/or Python are required. These should be documented, for example through a GitHub profile or similar. Familiarity with numerical methods for solving Maxwell’s equations, particularly in the context
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). Programming in C++ or Fortran and proficiency with MATLAB or Python scripting. Experience with tools for simulating chemical kinetic, e.g. Cantera or CHEMKIN. Background in compressible flows and applied
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advantage: Developing algorithms for CFD solvers (e.g. OpenFOAM). Programming in C++ or Fortran and proficiency with MATLAB or Python scripting. Experience with tools for simulating chemical kinetic, e.g
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awarded. Computer programming experience using languages such as for example Python or C++ is a requirement. It is an advantage with a master’s degree related to ALICE or ATLAS. Experience from working with
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condition of employment that the master's degree has been awarded. Computer programming experience using languages such as for example Python or C++ is a requirement. It is an advantage with a master’s degree
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the master's degree has been awarded. The candidate must have good knowledge in atmospheric dynamics. Proficiency in scientific coding and data analysis (e.g., Python, MATLAB, R, C++, FORTRAN) is required
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cycle processes, dynamics of oxygen and nutrient cycles, is required. Expertise in scientific scripting, programming, and data analysis (e.g., Python, Matlab, R) is required. Knowledge of climate
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. Experience in scientific programming (e.g., Matlab and Python) is a requirement. Experience with analysis of climate data sets is an advantage. Applicants must be able to work independently and in a structured
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using Python, R, Matlab, Julia or similar is required. Knowledge of energy systems, energy system modelling or the European energy market will be an advantage. Understanding of atmospheric processes