Dear MT experts, The European Commission is expanding the team behind its Machine Translation service, so far known as MT@EC <http://ec.europa.eu/dgs/translation/translationresources/machine_translation/index_en.htm>, in order to set up an eTranslation <https://ec.europa.eu/cefdigital/wiki/display/CEFDIGITAL/Machine+translation> platform as a core building block to be used by all online services that need cross-lingual functionalities within the Connecting Europe Facility (CEF) programme (more details here <https://ec.europa.eu/cefdigital/wiki/display/CEFDIGITAL/eTranslation+Background> ).
For building and improving MT engines, we are looking for experts with an advanced university degree in machine learning, data mining, statistical data modelling or computational linguistics, who are familiar with data-driven techniques for natural language processing, such as statistical MT, or have equivalent experience. We expect several years of professional experience in the area of natural language processing or MT, in-depth knowledge of setting up and evaluating MT software, and skills in evaluating MT quality. Prior experience in application of "deep learning" methods to data analysis and prediction, such as neural network toolkits like TensorFlow, Theano, or similar, will be considered as asset. The tasks will be performed on the Commission’s premises in Luxembourg (intra muros). The successful candidate will work on maintaining the current MT system, extending its coverage, improving the translation quality via incorporation of new methods, and adapting it to a cloud environment. The candidate will collaborate with a team of analysts, developers and computational linguists. For more information in the technical aspects of the project or if you are interested in working with us, please contact me via email <[email protected]>. Best regards, Andreas Eisele <[email protected]> Andreas Eisele European Commission Directorate-General for Translation (DGT) R.3 – Informatics Building ARIANE-B Office 03-B078 L-2920 Luxembourg Tel.: (+352) 4301-34718
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