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Engineering or a closely related discipline. Preferred Qualifications: Strong experience in one or more of the following: Numerical methods for ordinary and delay-differential equations. Scientific computing
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technical documentation in LaTeX. Specific Requirements Knowledge: Supercomputing architectures and their high-performance execution environments (High-performance computing). Numerical Methods: EDP solvers
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the predictions of this new configuration against existing theories (which model these structures in parallel) using synthetic case studies. These numerical tests will aim to clearly isolate the impact of
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modelling activity. Demonstrated expertise in finite-element methods or related numerical techniques. Experience in code development, HPC architectures, and parallel programming is highly desirable
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following areas: Machine Learning, Deep Learning, Reinforcement Learning, Data Mining; Programming; Parallel programming and High-Performance; Computing; Scientific computing, Numerical methods, and Numerical
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computing, such as Python and C. Training in one or several of the following areas: computational physics, numerical methods, signal processing, statistical inference or scientific data analysis. Ability
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initiative-taking, structured, persistent, and with good numerical ability Other qualifications For the doctoral programme in question, the following are considered as other qualifications: Experience working
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: Understand the relationship between POPs and the glacial environment: POPs will be characterised and quantified within different glacial substrates (snow, ice, water, cryoconite, sediments) and within