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of the developed cavitation model with acoustic radiation models, validating against experimental data. Required Qualifications A relevant educational background within Mathematics, Physics, or Engineering, with a
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, Mathematics, Applied Mathematics, Mathematical Engineering, or related fields. Proficiency in programming languages such as Python, R, or other programming languages. Familiarity with multi-agent systems
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The candidate should have experience with hydraulics, hydrology or urban drainage. Furthermore, excellent skills within mathematics, statistics, programming (Python, Matlab or other languages), and geographical
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to begin the PhD study in connection with the Master study. Thus a prerequisite for acceptance is that the candidate is enrolled in a relevant Master’s programme, such as Mathematical Engineering. The
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degree in computer science or a closely related field such as mathematics or control engineering. Due to the project’s angle, applicants should have a strong background in at least one of the following
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We seek PhD students that will contribute to new generations of scalable, model-based tools for cyber-physical systems based on a mathematical sound foundation, that enables trade-offs between
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relevant Master’s programme, such as Signal processing, Machine learning, Statistics, Mathematics, Acoustics, or similar. The integrated stipend consists of two parts, A and B. During part A you are enrolled
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science(e.g., mathematics, physics, computer science, etc.), a strong background in data science, statistics, or machine learning, and an interest in biomedicine. Alternatively, a candidate with a