Machine Learning Research for Sustainable Development Goals (NLP Track)
Mission and objectives
The United Nations Development Programme, Bureau for Policy and Programme Support (BPPS) has the responsibility for developing all relevant policy and guidance to support the results of UNDP’s Strategic Plan. BPPS’s staff provides technical advice to Country Offices; advocates for UNDP corporate messages, represents UNDP at multi-stakeholder fora including public-private dialogues, government and civil society dialogues, South-South and Triangular cooperation initiatives, and engages in UN inter-agency coordination in specific thematic areas. BPPS works closely with UNDP’s Crisis Response Unit (CRU) to support emergency and crisis response. BPPS ensures that issues of risk are fully integrated into UNDP’s development programmes. BPPS assists UNDP and partners to achieve higher quality development results through an integrated approach that links results based management and performance monitoring with more effective and new ways of working. BPPS supports UNDP and partners to be more innovative, knowledge and data driven including in its programme support efforts.
An SDG Integration Team located with UNDP’s Global Policy Network (GPN) offers a menu of services emphasizing direct short- to medium-term engagements to respond rapidly to requests from country offices for support on national implementation and monitoring of integrated policy solutions, qualitative and evidence-driven analysis for accelerated progress, and knowledge sharing and upscaling of innovative approaches to sustainable development. The team’s work emphasizes the application of evidence- driven data and analytics for SDG implementation and reporting. In this regard, advances in digital technology are creating data at unprecedented levels of detail and speed, turning the stories of people’s lives into numbers every minute of every day, across the globe. An important focus of the integration work is to complement traditional data (e.g., national statistics,) with new and alternative sources including digital ‘breadcrumbs,’ satellite data, social media to identify emerging trends and gain new perspectives on issues in development.
The team is looking for an experienced machine learning (ML) volunteer to support the team's research in the area of natural language processing (NLP) for Sustainable Development Goals (SDGs). The purpose of this assignment is to design, develop and test ML solutions for NLP problems in the area of SDGs. This is a research-intensive assignment that requires performing a range of tasks from literature review and prototyping models to model evaluation and writing up results. The research is expected to produce an industry-grade open-source model. Note that this is a highly selective opportunity. Your application must include a short motivation statement that clearly describes how your education and experience align with the task. You should include links to your GitHub, publications or online portfolio, if applicable.
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