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Nanyang Technological University

Project Officer (Linguistics/ Language studies/Data science)

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  • 8 days ago
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Job Description

We are looking to appoint a full-time Project Officer at the School of Humanities in Nanyang Technological University (NTU).

The incumbent will join the Linguistics and Multilingual Studies (LMS) Department working on a project titled Performance-interpretability Tradeoff in Discourse Research led by Professor Dennis Tay. The position is a fixed term post for 17 months.

About the Project

The performance-interpretability tradeoff (PIT) in data science and AI refers to the balance between how well a statistical/machine learning model performs, and how readily humans can comprehend it. This project investigates the nature and characteristics of PIT in discourse research, focusing on the following:

i) the (strategically) indeterminate nature of PIT

ii) PIT in time-based algorithms and discourses

iii) conceptual relationship(s) between PIT and mixed-methods discourse research, with subsequent developments based on emergent findings.

Discourse datasets to be investigated include psychological counseling, social media, academic lectures, and other relevant time-based contexts, while time-based algorithms include LSTM, ARIMA time series, and survival regression models. The project also aims to design and develop relevant pedagogical resources aimed at students and the general public.

Key Responsibilities:

  • Assist in sourcing and collecting language and discourse datasets across different domains
  • Assist in pre-processing discourse data for analysis
  • Assist in preparation of research output, pedagogical resources, and/or other project-related deliverables

Job Requirements:

  • Good Bachelor's degree in linguistics, language studies, data science, or related fields
  • Strong verbal and written communication skills
  • Working knowledge of Natural Language Processing and Python / R is an advantage

Interested applicants may apply with submission of the Curriculum Vitae.

We regret to inform that only shortlisted candidates will be notified.

Date Posted: 16/11/2024

Job ID: 100524277

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