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PhDs Transformation

Job in 9700, Groningen, Groningen, Netherlands
Listing for: Rotterdam School of Management, Erasmus University (RSM)
Full Time position
Listed on 2026-02-13
Job specializations:
  • Research/Development
    Economics, Research Scientist
Salary/Wage Range or Industry Benchmark: 60000 - 80000 EUR Yearly EUR 60000.00 80000.00 YEAR
Job Description & How to Apply Below
Position: PhDs Africa @ Work: Transformation of employment 1920 - 2020

PhDs Africa @ Work:
Transformation of employment 1920 - 2020

The Faculty of Economics and Business offers an inspiring study and working environment for students and employees. International accreditation enables the Faculty to assess performance against the highest international standards. It also creates an exciting environment of continuous improvement. FEB's programmes, academic staff and research do well on various excellence ranking lists.

FEBRI, the graduate school and research institute of the Faculty of Economics and Business has available two PhD positions for the project Africa @ Work:
Transformation of employment 1920 - 2020
embedded within the ERC Consolidator Grant project AWORK

What are you going to do?

Project 1 examines how urbanisation in Africa has reshaped where people work, the kinds of jobs they do, and the opportunities available to them over the long run. Using population censuses and labour surveys, the project reconstructs long‑run changes in the location and structure of employment, tracking rural–urban migration, sectoral shifts, and labour market responses to periods of economic expansion, crisis, and structural adjustment.

Focusing on Zambia, Angola, and Côte d’Ivoire, the project compares how different development paths have produced distinct urban labour markets. In some contexts, urban growth has been driven by natural resource booms, shifting labour away from agriculture into state‑related and service activities with limited productivity gains. In others, urbanisation has emerged from rising agricultural productivity or rural pressures, generating more diverse forms of work in trade, transport, and services.

The central question is whether urbanisation has translated into productive and sustainable employment, or instead reproduced new forms of vulnerability and informality.

Project 2 examines how gender inequalities in African labour markets emerged, how they evolved over time, and why they remain so persistent. Using population censuses, labour reports, and agricultural surveys, the project reconstructs long‑run patterns of women’s and men’s participation across formal employment, informal work, own‑account activities, and unpaid family labour, making visible forms of work that were often poorly recorded or overlooked.

Focusing on Kenya, Uganda, and Botswana, the project compares how different economic systems—a settler economy, a peasant cash‑crop economy, and a mining‑based economy—produced distinct gendered labour regimes. In Kenya, women’s labour was central to settler agriculture yet systematically undervalued; in Uganda, men dominated cash‑crop production while women remained concentrated in subsistence farming and local trade; and in Botswana, mining‑led growth generated formal employment largely inaccessible to women, pushing them into low‑income urban activities.

The central question is how these historical labour regimes shaped access to work, income, and security, and why gender gaps in employment persist even as African economies transformed.

Requirements

The ideal candidates have:

  • Obtained a MSc degree (or equivalent) in Economics, Economic History, Development Economics, or Spatial Sciences, or a closely related field, with excellent results.
  • A clear interest in economic history, long‑run development, and processes of structural change over time, particularly in low‑ and middle‑income countries.
  • Affinity with one or more of the following areas: development economics, economic history, urbanisation, inequality, or spatial analysis.
  • An interest in working with archival and other primary sources, and the ability or willingness to develop skills in working with large and sometimes fragmented historical datasets, including linking historical and contemporary data.
  • Experience with, or a strong willingness to develop skills in, quantitative data analysis, with Python, Stata, or R or experience working with GIS software (experience with at least one of these is preferred).

You also have:

  • Excellent command of English, both written and spoken.
  • Strong analytical skills, intellectual curiosity, and the ability to work both independently and collaboratively within an…
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