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research questions, and be able to think critically and develop your own scientific ideas. Previous experience with statistical analysis, programming (e.g., R or Python), machine learning, or genomic data
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and renewable fuel production. You have experience with process-modelling tools such as Aspen Plus, Aspen HYSYS or other related software and are motivated to develop and apply dynamic models of energy
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, and you are interested in applying these disciplines to Power-to-X and renewable fuel production. You have experience with process-modelling tools such as Aspen Plus, Aspen HYSYS or other related
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their skills and experience. Current priority areas for A&A are: State preparation techniques Schemes for extracting information and observables from quantum computation Noise modelling of logical quantum
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controlled systems and hydraulic transformers Hands-on experience with experimental setups and laboratory testing of electro-hydraulic systems Familiarity with embedded systems or real-time control
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system configurations, experimental setups and operational data. The scientific ambition is to develop methods that combine physical models and data-driven approaches for adaptive, real-time operation of
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). Experience with radar measurements, remote sensing, glaciology, or scientific programming is an advantage but not a requirement. Proficiency in English is required. We value curiosity, initiative, and an
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to qualify (which is 2 years) Highly skilled in numerical modelling and programming is essential Experience with at least two of the following disciplines is expected: o hydrological and/or land surface models
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to molecular hydration. The student will develop experimental methodologies and combine these with state-of-the-art characterization techniques, including Magnetic Resonance Imaging (MRI), Nuclear Magnetic
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degree in computer science, mathematics, statistics, physics or relevant fields. Strong background in machine learning, preferably experience in probabilistic modeling, Bayesian machine learning, or graph