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five years of receiving their PhD. In particular for this position, the following is required: PhD in the fields of economics with a thesis subject relevant to the description of the tasks outlined
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for this position, the following is required: PhD in a relevant field such as data science, AI, computer science, machine learning, Earth system science, climate etc. with a thesis subject relevant to the description
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for this position, the following is required: PhD in a relevant field such as computer science, quantum physics, electronic engineering, data science, AI, machine learning, Earth system science, climate etc. with a
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Observation Programmes and in particular with the Copernicus Hyperspectral Imaging Mission for the Environment (CHIME) project and Mission Science team. You will be part of the ESA Φ-lab. Our mission is to
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their PhD are preferred. Additional requirements Cross-cultural sensitivity. The working languages of the Agency are English and French. A good knowledge of one of these is required. Knowledge of another
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Location ESOC, Darmstadt, Germany Our team and mission You will join the Ground Segment System and Cybersecurity Engineering Section in the System and Applications Engineering Division, Ground
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, the following is required: PhD in high-speed aerodynamics, turbulence, transition and combustion modelling, or another relevant aerospace engineering discipline. Additional requirements In addition to your CV and
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by candidates within five years of receiving their PhD. In particular for this position, the following is required: PhD in engineering (space engineering in particular) and/or a PA discipline
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learning for dynamical systems, system identification and control systems. This can involve co-tutoring of PhD students or early R&D cooperative studies. contributing to the development of advanced benchmark
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for this position, the following is required: PhD in systems engineering, computer science or informatics, and the subject of the thesis should be relevant to the task description provided above (e.g. digital twin