Applying Natural Language Processing for SDGs Analysis

Contract

This is a UNV contract. More about UNV contracts.

The online volunteers will participate in the implementation of an ongoing project, applying Natural Language Processing to analyze and classify textual data related to the SDGs. The selected candidates will have an opportunity to choose the specific workstream which aligns with their interest and work as part of a developer team under the SDG AI Lab guidance. The assigned tasks may include data preparation (cleaning and annotating), model selection, feature engineering, syntactic and semantic analysis. SDG AI Lab will support the volunteer as needed, with a bi-weekly check-in and maintaining collaboration through MS Teams and GitHub group repository. The volunteer will work under the coordination of the Technical Specialist of the IICPSD.

• Technology development

• Information technology and telecommunications

  IICPSD’s SDG AI Lab (sdgailab.org) initiative requires assistance in developing and applying algorithms to support the research and digital solutions development. The project is focusing on analyzing and deriving insights from text-based sources, while there will also be exploratory activities on ML-based solutions for international development. The lab provides in-house expertise, resources, and research support to various projects to mainstream digital transformation on the current development problems and to contribute towards the achievement of the Sustainable Development Goals. The ideal candidate for this volunteer position is a person with experience in a coding project (including personal and school) and git source control.

• Volunteers: 24 needed

• 11-20 hours per week / 13 weeks

  Bachelor’s in computer science, electrical engineering, mathematics, statistics, or related field with a strong interest in data science; Background knowledge and ability to grasp techniques such as text mining, sentiment analysis, text extraction, topic classification, data visualization, and ML modelling; Applied knowledge of programming languages, such as Python or Java, as well as experience of open-source software library such as TensorFlow, Scikit-Learn, Pandas, Gensim, spaCy and NLTK;

• Global

• English