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, medicine and semiconductor products such as microchips and solar cells. Such fluid measurements also find application in environmental monitoring and e.g. medical infusion systems in neonatal care. In
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. Faculty Mechanical Engineering From chip to ship. From machine to human being. From idea to solution. Driven by a deep-rooted desire to understand our environment and discover its underlying mechanisms
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personalised training programme will be set up reflecting your training needs and career objectives. About 20% of your time will be dedicated to this training component, which includes following courses and/or
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training programme will be set up reflecting your training needs and career objectives. About 20% of your time will be dedicated to this training component, which includes following courses and/or workshops
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as we find a suitable candidate, we will arrange an interview. We therefore recommend to apply at your earliest convenience. The starting date can be agreed upon after the interview, but will
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, rendering such models robust. The PhD project aims to go the next step, closing the loop between failure and adaptation by developing resilient machine learning. The developed methods will detect when
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called complex dynamical systems. Under the supervision of Prof. Han Peters your goal is to find a measure theoretic description of the chaotic behaviour arising in these dynamical systems. While the wider
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You can apply only via the button below. Address your letter of application to Prof. dr. N. Keijsers. In the application form, you will find which documents you need to include with your application. We
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advanced detection tools that visualize cellular stress responses, this approach allows you to map how individual’s background translate into toxicodynamic variability. The project serves as a proof of
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. In the application form, you will find which documents you need to include with your application. We look forward to receiving your application. The first interviews will take place on Monday 9