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PhD Studentship in Term Extraction for Under-resourced Languages

Location: NUI Galway
Level: PhD

Anticipated start date: September 2021 / October 2021
Stipend: €18,500 per annum (non taxed) plus university fees
Closing Date: 21st May 2021
Full Role Description
?Application instructions below
Why ADAPT?

Contribute to the ADAPT research agenda that pioneers and combines research in AI driven technologies: Natural Language Processing, Video/Text/Image/Speech processing, digital engagement & HCI, semantic modeling, personalisation, privacy & data governance.
Work with our interdisciplinary team of leading experts from the complementary fields of, Social Sciences, Communications, Commerce/Fintech, Ethics, Law, Health, Environment and Sustainability.
Leverage our success. ADAPT’s researchers have signed 43 collaborative research projects, 52 licence agreements and oversee 16 active commercialisation funds and 52 commercialisation awards. ADAPT has won 4JUdGzvrMFDWrUUwY3toJATSeNwjn54LkCnKBPRzDuhzi5vSepHfUckJNxRL2gjkNrSqtCoRUrEDAgRwsQvVCjZbRyFTLRNyDmT1a1boZVfunding. Additionally, six spinout companies have been formed. ADAPT’s researchers have produced over 1,500 journal and conference publications and nearly 100 PhD students have been trained.
As an ADAPT funded PhD researcher you will have access to a network of 85 global experts and over 250 staff as well as a wide multi-disciplinary ecosystem across 8 leading Irish universities. We can influence and inform your work, share our networks and collaborate with you to increase your impact, and accelerate your career opportunities. Specifically we offer:

Opportunity to build your profile at international conferences and global events.
A solid career pathway through formalised training & development, expert one-on-one supervision and exposure to top specialists.
A Fully funded, 4 year PhD postgraduate studentship which includes a stipend of (€18,500 per annum – non taxed), along with equipment, annual travel funding
Funding for annual student fees
Context

Term Extraction for Under-resourced Languages: Terminology is a key part of understanding texts from specific domains and analysing digital content at a large scale. Term extraction is the task of finding terms where they are used in text and this task has largely been applied only to a few majority languages such as English. For under-resourced languages, including Irish, there is comparatively little study of this task and gold standard corpora are missing or very small. The student will develop an approach that takes a transfer learning approach using the resources that are available for major languages, such as English, and applying this to under-resourced languages and scenarios. In addition to transferring annotations, the student will investigate approaches that are based on meta-learning to create classifiers for multi-word expression which distinguish n-grams into terms and non-terms. Further this approach will develop models that can compose word embeddings of multi-word expressions and deduce whether there is a compositionality to the meaning, and hence whether the n-gram represents a term, based on our previous models for this task. This work will provide students with a deep understanding of artificial intelligence and natural language processing that will equip the students for their further career in industry or academia.

Minimum qualifications

Candidates for this position should have a MSc or equivalent in a relevant field of study with an emphasis on areas such as machine learning, natural language processing or linguistics.
Preferred qualifications

The candidate should have good programming skills in Python or Java (and preferably experience with Tensorflow or other deep learning tools).
Application Process

The candidate will be based in the Data Science Institute (DSI) of the National University of Ireland, Galway.

Send your application (CV and cover letter, both in PDF only) by 21st May 2021 to Dr. John P. McCrae [email protected].
Diversity

ADAPT is committed to achieving better diversity and gender representation at all levels of the organisation, across leadership, academic, operations, research staff and studentship levels. ADAPT is committed to the continued development of employment policies, procedures and practices that promote gender equality. On that basis we encourage and welcome talented people from all backgrounds to join ADAPT.

Apply

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