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Support in applying Natural Language Processing Techniques to Sustainable Development Goals Analysis

UNDP Istanbul International Center for Private Sector in Development

16 Oct 2020 Apply now Share
16 Oct 2020 Apply now Share
Background and objectives
The Online Volunteers will participate in developing and applying machine learning processes, particularly in the field of Natural Language Processing to analyze and classify textual data related to development and the Sustainable Development Goals (SDGs). The Online Volunteers will have an opportunity to choose the specific project they would like to join and form a team under SDG AI Lab supervision. The Online Volunteers are expected to do data processing, converting unstructured records into a structured format, data annotation, data cleaning and applying unsupervised and supervised machine learning algorithms if applicable. SDG AI Lab will support the Online Volunteers as needed, with a bi-weekly check-in via Zoom and maintain a connection through MS Teams and GitHub Repository. The Online Volunteers will work under the coordination of the Technical Specialist of IICPSD.
Technology development
Information technology and telecommunications
IICPSD’s SDG AI Lab initiative ( requires assistance in enhancing and applying solutions to support the research and digital transformation in the development sector. The assignment involves an exploration of how to deploy ML-based solutions on development issues; particularly analyzing and derive insights from text-based sources using Natural Language Processing. The Lab provides in-house expertise, resources, and research support to various UNDP projects to mainstream digital transformation to development problems and to contribute to the achievement of the Sustainable Development Goals.
Volunteers: 15 needed
11-20 hours per week / 13 weeks
Bachelor’s in Computer Science, Electrical Engineering, Mathematics, Statistics, or related field with strong interest in Data Science; Understanding and knowledge of analytical techniques such as text mining, image processing, predictive analysis, event detection, data visualization, and proven machine learning modeling; 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, and NLTK;

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