PAL Network 2026 Research Fellowship
Job Description
The PAL Network Research Fellowship Programme is designed to foster innovative, policy-relevant, and equity-focused research that advances foundational learning across the Global South. The programme supports researchers in generating actionable insights using citizen-led assessment data to better understand the factors shaping children’s learning outcomes, educational participation, and inequities.
The 2026 Fellowship Cohort focuses specifically on analysis of PAL Network’s 2025 International Common Assessment of Numeracy (ICAN) and International Common Assessment of Reading (ICAR) datasets, collected through nationally representative household-based assessments across 11 countries. Unlike many school-based assessments, ICAN and ICAR capture both in-school and out-of-school children and include rich contextual, household-level, and demographic information that enable deeper exploration of learning inequalities and their drivers.
The PAL Network Research Fellowship Programme aims to generate innovative and policy-relevant evidence to improve children’s foundational learning. The fellowship seeks to strengthen research capacity, promote creative and interdisciplinary analysis of large-scale learning data, foster collaboration across researchers and institutions, and support the use of evidence to inform educational policy and practice. Through mentorship, partnerships, and knowledge-sharing, the programme encourages research that advances equitable, scalable, and sustainable approaches to improving foundational learning outcomes for all children, particularly those from marginalized and underrepresented groups.
1. Fellowship Duration & Time
The 2026 PAL Network Research Fellowship will run for approximately 3 to 5 months, beginning in July 2026. The exact duration may vary depending on the scope and complexity of each proposed research project.
2. Number of Fellows
PAL Network expects to select approximately 4 to 6 fellows for the 2026 cohort. Fellows may come from diverse academic, professional, and geographic backgrounds, with strong interest and expertise in foundational learning, education data, public policy, statistics, economics, development studies, or related fields.
3. Research Focus Areas
The 2026 fellowship cohort will focus on innovative analysis of PAL Network’s 2025 International Common Assessment of Numeracy (ICAN) and International Common Assessment of Reading (ICAR) datasets collected across 11 countries. Fellows are encouraged to explore research themes related to:
- Explore under-researched dimensions of learning inequality;
- Use comparative cross-country approaches;
- Connect learning outcomes with contextual and policy variables;
- Integrate external datasets or policy indicators, where possible;
- Examine structural drivers of learning disparities;
- Generate actionable insights for policy and programming.
Application Process
Application Requirements:
- A completed online application form;
- A current Curriculum Vitae (CV) highlighting relevant academic, research, and professional experience;
- A maximum two-pages research proposal based on PAL Network’s ICAN/ICAR 2025 datasets.
Applicants are expected to access and review the publicly available ICAN/ICAR 2025 microdata and accompanying documentation hosted on the DataFirst platform prior to submitting their proposal.
The proposal should clearly outline:
- Proposed title;
- Research question(s) or analytical focus;
- Rationale and policy relevance;
- Proposed methodology and analytical approach;
- Key variables, dimensions, or datasets of interest;
- Expected contribution to foundational learning research, policy, or practice;
- Planned outputs during the fellowship period.
Applicants are encouraged to propose innovative and policy-relevant analyses, including comparative, equity-focused, interdisciplinary, or cross-dataset approaches.
Eligibility Criteria:
The specific eligibility criteria will be tailored for each research fellowship position and type of fellowship offered. However, the following general criteria will be considered an asset for all applicants:
- Academic Background: Completed or in-progress master’s or doctoral program in education measurement, data science, statistics, development studies, public policy, economics, or related fields. Undergraduate degrees with proven record of work experience will also be considered.
- Strong technical expertise in quantitative data analysis, with proficiency in Stata, R, or Python.
- Experience working with large-scale learning assessments or education datasets.
- Demonstrated ability to manage data systems and produce high-quality analysis and reporting.
- Excellent written communication skills and ability to present complex data in accessible formats.
- Prioritize applicants from the global south or those with experience working in these contexts. Understanding the unique educational challenges and opportunities in these regions is crucial.