-
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
-
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
-
, mathematics, engineering, or a field relating to data science with emphasis on statistical modelling. You are required to have: Experience with statistical modelling Strong programming skills in one of the main
-
science, statistical analysis, and mathematics. Experience with programming languages such as MATLAB and Python. Excellent analytical, problem-solving, and modeling skills. Strong written and verbal
-
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
-
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
-
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
-
Postdoc in statistics to develop Bayesian privacy metrics for synthetic health data (2024-224-05725)
. Qualification requirements: You should hold a PhD degree in computer science, statistics, physics, mathematics, engineering, or a field of science relating to data science with emphasis on statistical
-
proper decisions. The trade-off between safety and greediness are assessed using stochastic constrained optimization. At the outset, it is assumed that the mathematical model of the system is known