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sensing provides large-scale and consistent observations, in-situ data collection remains a vital component for ground-truthing, model calibration, and validation of automated monitoring. However
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information General interest in space and space research Behavioural competencies Education You should have recently completed, or be close to completion of a PhD in a related technical or scientific
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to build predictive models Collaborate closely with experimentalists and modelling experts Project Environment This position is part of a collaborative research project involving: Two PhD students at TU
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individual choices model gives you some freedom to assemble your own set of terms and conditions. Candidates from outside the Netherlands may be eligible for a substantial tax break. Leiden University is
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your personal motivation and qualifications for the position (maximum two A4s). Curriculum vitae, including the contact information of three referees. Lists of courses followed (at M.Sc. level) including
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particular for this position, the following is required: PhD in engineering or physics, preferably with a focus on the development of thermal fluid-structure interaction mathematical models. A thesis topic
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PhD in a related technical or scientific discipline. Preference will be given to applications submitted by candidates within five years of receiving their PhD. In particular for this position
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to keep the data up-to data with very little effort. Estimate energy and land needs for the realization of the CCU potential. Develop a multi-objective optimization model for individual CCUS projects
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, Computer Science and Artificial Intelligence. The position is embedded in the Multi-Agent Systems group of the department of Artificial Intelligence of the Bernoulli Institute. Qualifications PhD in Computer Science
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For information you can contact: Davide Grossi (information about the position), d.grossi@rug.nl (please do not use the email addresses above for applications) For more information about the project and other