INTERNSHIP IN THE FIELD OF AUTOMATIC TOOLS FOR MULTILINGUAL LEARNER CORPUS CREATION
Descrizione dell'offerta di lavoro
One of the project goals is to create a multilingual learner corpus of student essays.
The project involves the collection, annotation, and analysis of student essays written by language learners and aims to support research at the intersection of research on multilingualism, corpus linguistics and natural language processing (NLP).
The focus of the internship lies on the normalisation/correction of learner texts, contributing to the linguistic enrichment of the corpus.
The internship will involve researching, selecting and implementing existing approaches for grammatical error correction (GEC) and evaluating their performance on learner data from the project.
The work will offer hands-on experience in corpus annotation, tool evaluation, and applied NLP for educational data, with a view on modern cross-linguistic/multilingual approaches in the field.
Requirements Background in corpus linguistics, computational linguistics, or natural language processing Familiarity with learner corpora, grammatical error correction, or related fields Experience with Python, NLP libraries (e.
.
spaCy, HuggingFace, NLTK), or annotation tools is a plus Good organizational skills and attention to detail Good command of English and German We offer Duration.
2-3 months Location.
on-site presence at premises of Eurac Research Bolzano is required Start date.
Flexible Supervision and support will be provided by researchers on the project team and the language technologies research group, exchange meetings with other institute members can be organised on interest.
Extra-curricular student retribution can be arranged through Erasmus+ internship bursaries (only for international students).
Curricular internships are welcome, if the applicant is affiliated with an Italian University, but no payment is foreseen.
Internal funds can be arranged when curricular and Erasmus+ internships are not possible, and will depend on the candidate's academic background.
How to Apply Please send your application by , including.
a short motivation letter (max.
1 page) your CV (highlighting relevant coursework or experience) optionally, a brief example of previous work related to NLP or corpus annotation
Dettagli dell'offerta
- Eurac Research
- 24/07/2025
- 04/01/2026
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