The Population Division was created in 1946 with the mandate of strengthening the capacity of the international community to address current and emerging population issues and to integrate population dimensions into the development agenda at the national and international levels.
Within the overall framework of the Department, the Population Division is responsible for analytical, normative and capacity-building activities in the field of population.
The Division provides substantive support to the Commission on Population and Development and to other intergovernmental bodies as appropriate.
The Division is engaged in the organization of technical meetings, and the preparation of technical documentation on a vast array of population subjects of interest to Member States.
The Population Division is organized in thematic sections and units focusing on various demographic aspects.
The Front Office, led by the Director and two Branch Chiefs, oversees three specialized Units (Programme Management; Publications, Outreach and Support; Population Data) and two branches: the Population Policies and Development Branch and the Population Trends and Analysis Branch.
The former comprises the Fertility and Population Ageing Section and the Migration and Urbanization Section, both of which analyze and assess policies and trends in their respective areas, and organize expert meetings.
The latter branch includes the Demographic Analysis Section, which develops demographic methods and analyses, and the Population Estimates and Projections Section, focusing on global population estimates and projections.
Lastly, the Demographic Data Systems Unit maintains the Division’s IT infrastructure, manages major databases, and supports data dissemination.
Each unit and section contributes specialized expertise, playing a vital role in the Division’s overall function.
Under the general guidance of the team manager within the respective section, the intern may provide support in the following areas:
The specific research topics and assignments will be defined based on discussion between the intern and the responsible officer and should be mutually beneficial for both the intern and UN.
The intern may also be asked to assist in the day-to-day work of the Division if required.
The intern is expected to familiarize him/herself, to a limited extent, with administrative work of the division and other tasks that are typical of UN organizations.
Upon completion of this internship, the intern will prepare a brief report and make a presentation to the Division on the experience gained, and any potential substantive research paper that this internship might lead to.
Qualifications/special skills
Applicants must meet one of the following requirements:
(a) be enrolled in, or have completed, a graduate school programme (second university degree or equivalent, or higher);
(b) be enrolled in, or have completed, the final academic year of a first university degree programme (minimum bachelor’s degree or equivalent).
Applicants to the UN Internship Programme are not required to have professional work experience.
However, a field of study that is closely related to the type of internship that you are applying for is required.
For this internship, applicants should be pursuing their studies preferably in demography, population studies, human geography, public health, international relations, political science, development studies, quantitative history, digital humanities, applied statistics or related area.
Applicants must be a student in the final year of the first university degree (bachelor or equivalent), Master’s or Ph.D. Programme or equivalent, or have completed a Bachelor’s, Master’s or Ph.D. Programme.
Do you meet any of the above criteria? If yes, please indicate which one and attach proof to the application.
Please note that you will have to provide an official certificate at a later stage.
Applicants should be computer literate in standard software applications, especially MS Excel.
Proficiency with R statistical software programming is desirable.
Familiarity with population and vital statistics data and with demographic estimation methods is desirable.
Experience with scientific computing/statistical modelling is desirable.
Languages
DEADLINE: AUGUST 17, 2025