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Field
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bring a high level of appreciation for the accuracy and precision in lab analysis. Ideally you have some experience in working with ICP-MS or other Mass Spectrometry techniques. Project B: You have a MSc
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learning, e.g. using JAX, based on numerical models such as Higher Order Spectral method, mcsimpy, etc. Collect real metocean data from relevant online databases, datastreams such as from R/V Gunnerus, and
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. using JAX, based on numerical models such as Higher Order Spectral method, mcsimpy, etc. Collect real metocean data from relevant online databases, datastreams such as from R/V Gunnerus, and experimental
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IMPRS-ML, our students can participate in numerous advanced courses, lectures and workshops offered by our university partners. Moreover, students are encouraged to participate in external training
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offers a stimulating scientific environment in which research focuses mainly within the research programmes (1) Algebra, Geometry and Mathematical Physics, (2) Pure, Applied and Numerical Analysis, and (3
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in thermodynamics, optimization, and control theory. Strong understanding of mathematical modeling, numerical optimization, and/or model predictive control (MPC). Experience working with large-scale
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operation costs significantly. Besides, there is an opportunity to explore the commercialisation paths of the developed smart sensor prototype. You will gain from the experience in numerous ways, whether it
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deploy these technologies in the industry context without the need for big datasets. You will gain from the experience in numerous ways, whether it be transferable skills in the technical area of
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. Strong knowledge of quantitative and/or computational research methods, ideally in econometric analysis or optimization and simulation models. Preferable knowledge in Python and STATA. A collaborative team
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, Applied Mathematics, or a related field. Strong foundation in computational modelling & numerical simulations The laboratory The Decision and Bayesian Computation (DBC) – Epiméthée (EPI) laboratory