Postdoctoral Fellow Connected to the Research of CHAIN
About the position
At the Department of Sociology and Political Science (ISS) there is a vacant temporary position as Postdoctoral Fellow for a period of four years. The position is connected to the research of CHAIN (Centre for Global Health Inequalities Research), but the post doc will also collaborate closely with the AI-Lab at NTNU and UNICEF.
Job description and responsibilities
The post doc will mainly focus on CHAIN’s first and second mission: to monitor and explain global health inequalities and their determinants, by exploiting opportunities in the larger ecosystem of data innovation at UNICEF (data science/AI), including geospatial analysis of health coverage, schools and other socioeconomic determinants. Research stay(s) at UNICEF Head Quarters in New York will therefore be necessary. Other responsibilities may include analytical assistance to the growing team of CHAIN researchers.
Researchers, policymakers and health practitioners have typically relied on survey or administrative register data to examine trends in, and causes of, socioeconomic inequalities in health (e.g., self-rated health, healthcare utilization, drug prescriptions, mortality, etc.). There are well-known problems with these data sources, however, and some of the challenges have grown larger in recent years. In high-income countries, it has become increasingly difficult to get high enough response rates in many large-scale surveys, causing problems with representativeness and generalizability.
Moreover, soaring economic costs and complicated privacy issues are recurring difficulties while trying to gain access to administrative register data sources. In low-and middle-income countries (LMICs), administrative register data are most often unavailable, and survey information can be difficult, or impossible, to collect in conflict areas. Survey data are available in non-emergency/humanitarian areas, but the economic costs of data collection in LMICs remain a challenge, and especially so when longitudinal information (i.e., several panel waves covering numerous years) is needed. Furthermore, the quality, completeness, and granularity of survey data is always a cause of concern. Consequently, access to high-quality information is a pressing issue for both practitioners and researchers.
To make better use of naturally occurring data sources – or more precisely: privately captured digital exhaust data (such as mobile phone usage) – is therefore a potential avenue for those interested in population health and its distribution. Recent advances within machine learning techniques, and artificial intelligence (AI) more broadly, furthermore implies that we are able to process large amounts of data more efficiently than ever before. These analytical tools can be used to compile, combine and systematize both textual and numerical data points in ways that (potentially) offer new insights into longstanding research questions. Thus, this project further aims to strengthen the collaboration between researchers and implementers interested in addressing health inequalities, on the one hand, and big data/machine learning/AI, on the other hand.
The post doc will pursue the following four overarching research strands in a collaboration between UNICEF and NTNU (AI-Lab and CHAIN): (i) Examining socioeconomic inequalities in big data coverage and its consequences for external validity. (ii) Linking of data sources on health outcomes of children (e.g., premature mortality, healthcare utilization, malnutrition) and information on the socioeconomic circumstances of their families (e.g., poverty depth, parental educational attainment and -economic activity), and to develop new methods for the identification of causal links between them. (iii) Developing and (re-)testing of algorithms for estimating the association between socioeconomic indicator(s) and child health and mortality. (iv) Making empirical findings actionable and develop tools to be used by health practitioners to improve population health and address socioeconomic inequalities in health. Evidence might inform prioritization in planning, resource allocation and targeting of service delivery, for instance.
These four research strands should preferably be developed in tandem, but it is natural to first prioritize research strand (i), at least during the initial phase of the collaboration. We primarily expect outcomes in the form of scientific publications from research strands (i) and (iii), whereas research strand (ii) is mostly concerned with capacity and network building. To develop new and valuable tools for research strand (iv) is the overarching goal of this collaboration.
Applicants will be assessed by the (1) quality and potential of the project proposal, (2) quality and relevance of the academic works and (3) potential to contribute to the research group and the Department.
Required selection criteria
A postdoctoral research fellowship is a qualification position in which the main objective is qualification for work in academic positions. We require a completed Norwegian PhD in sociology, political science (or other relevant fields for the project tasks, such as computer science, machine learning, demography, statistics, or AI), or an equivalent foreign PhD approved as equivalent to a Norwegian PhD.
- skills in quantitative data management and statistical analysis
- good communications skills in English, both written and oral
If, for any reason, you have taken a career break or have had an atypical career and wish to disclose this in your application, the selection committee will take this into account, recognizing that the quantity of your research may be reduced as a result.
The appointment is to be made in accordance with the regulations in force concerning State Employees and Civil Servants and national guidelines for appointment as PhD, post doctor and research assistant.
Importance is attached to personal skills such as independence, well-organized, initiative, cooperative spirit, and motivation to contribute to a good working and social environment.
In the evaluation of which candidate is best qualified, emphasis will be placed on education, experience and personal suitability, and motivation for the position.
- exciting and stimulating tasks in a strong international academic environment
- an open and inclusive work environment with dedicated colleagues
- favourable terms in the Norwegian Public Service Pension Fund
- employee benefits
Salary and conditions
The employment period is 4 years.
Postdoctoral candidates are placed in code 1352, and are normally remunerated at gross from NOK 545 300 per annum before tax, depending on qualifications and seniority. From the salary, 2% is deducted as a contribution to the Norwegian Public Service Pension Fund.
The engagement is to be made in accordance with the regulations in force concerning State Employees and Civil Servants, and the acts relating to Control of the Export of Strategic Goods, Services and Technology. Candidates who by assessment of the application and attachment are seen to conflict with the criteria in the latter law will be prohibited from recruitment to NTNU. After the appointment you must assume that there may be changes in the area of work.
It is a prerequisite you can be present at and accessible to the institution daily.
About the application
The application and supporting documentation to be used as the basis for the assessment must be in English or a Scandinavian language.
Publications and other scientific work must follow the application. Please note that applications are only evaluated based on the information available on the application deadline. You should ensure that your application shows clearly how your skills and experience meet the criteria which are set out above.
- A project proposal of max. 5 pages, including a progress plan for the project.
- A comprehensive overview of all academic work.
- Relevant samples of publications (no more than five).
- CV, certificates and diplomas.
Joint works will be considered. If it is difficult to identify your contribution to joint works, you must attach a brief description of your participation.
NTNU is committed to following evaluation criteria for research quality according to The San Francisco Declaration on Research Assessment - DORA.
A good work environment is characterized by diversity. We encourage qualified candidates to apply, regardless of their gender, functional capacity or cultural background.
The city of Trondheim is a modern European city with a rich cultural scene. Trondheim is the innovation capital of Norway with a population of 200,000. The Norwegian welfare state, including healthcare, schools, kindergartens and overall equality, is probably the best of its kind in the world. Professional subsidized day-care for children is easily available. Furthermore, Trondheim offers great opportunities for education (including international schools) and possibilities to enjoy nature, culture and family life and has low crime rates and clean air quality.
As an employee at NTNU, you must at all times adhere to the changes that the development in the subject entails and the organizational changes that are adopted.
Information Act (Offentleglova), your name, age, position and municipality may be made public even if you have requested not to have your name entered on the list of applicants.
Further information concerning this post may be obtained from Professor Terje Andreas Eikemo, email: Terje.Eikemo@ntnu.no. For information about the application process please contact Renate Lillian Johansen at HR-section, e-mail: firstname.lastname@example.org
Please submit your application electronically via jobbnorge.no with your CV, diplomas and certificates. Applications submitted elsewhere will not be considered. Applicants with a diploma from a foreign university are advised to provide an explanation of the university's grading system.
If you are invited for interview you must include certified copies of transcripts and reference letters. Please refer to the application number SU-528 when applying.
Application deadline: 15.03.2021
NTNU - knowledge for a better world
The Norwegian University of Science and Technology (NTNU) creates knowledge for a better world and solutions that can change everyday life.
Department of Sociology and Political Science
We conduct research, teaching and dissemination in sociology, political science, media, communication and information technology, and sport sciences. The Department offers five-year master’s programmes in teacher education (lektorutdanning) in social sciences as well as in physical education and sports. As a social science department we have a special obligation to contribute to the public debate on important social issues. The Department of Sociology and Political Science is one of seven departments in the Faculty of Social and Educational Sciences.
Deadline 15th March 2021
Employer NTNU - Norwegian University of Science and Technology
Place of service Dragvoll