158 machine-learning "https:" "https:" "https:" "https:" "Eindhoven University of Technology (TU" positions at European Space Agency in Netherlands
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are encouraged to visit the ESA website: http://www.esa.int Field(s) of activity for the internship Topic of the internship: Artificial Intelligence / Machine Learning for ECSS space standards requirements
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-assisted translation (CAT) tools and neural machine translation to support the translation process. It consists of 24 team members and comprises three sections: The English Translation, Editing and Support
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competencies Education You should have completed within the past five years or be close to completing a PhD in a relevant field such as data science, AI, computer science, machine learning, Earth system science
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variations). As part of the laboratory activities, new challenges are identified: in particular, the use of Machine Learning techniques to predict atomic clock anomalies based on the processing of its
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wind speed and sea ice extent. The baseline algorithms designed to estimate such variables from the observed data at Level 1 (L1) are based on Machine Learning (with the exception of that for Freeze/Thaw
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) Topic 4: On-board Digital Signal Processing and Machine Learning/Artificial Intelligence The objective of this topic is to model and implement functions commonly used in on-board processing, assessing
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policies, administration, service level agreements and workflow process. Candidates interested are encouraged to visit the ESA website: http://www.esa.int Field(s) of activity for the internship Topic
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are encouraged to visit the ESA website: http://www.esa.int Field(s) of activity/research for the traineeship As an ESA Graduate Trainee, you will support the HR Department's teams dealing with
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of turning cutting-edge machine learning into operational environmental monitoring from space—and you enjoy balancing scientific depth with practical constraints—this internship is for you. Behavioural
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activities. Candidates interested are encouraged to visit the ESA website: http://www.esa.int Field(s) of activity for the internship Topic of the internship: Improving Learning from Experience in Space