Data Science Research Assistant

The data science and AI division at CSE is recruiting a research assistant for a project in Deep Learning for Predicting Poverty from Satellite Images.

The position is advertised within the research project Poverty traps in Africa, funded by FORMAS. FORMAS is a government research council for sustainable development. Its areas of activity include the environment, agricultural sciences, and spatial planning.

Information about the division and the project
About 900 million people - one-third in Africa - live in extreme poverty. Operating on the assumption that life in impoverished communities is fundamentally so different that it can trap people in cycles of deprivation (`poverty traps'), major development agencies have deployed a stream of development projects to break these cycles (`poverty targeting'). However, scholars are currently unable to answer questions such as in what capacity do poverty traps exist; to what extent do these interventions release communities from such traps --as they are held back by a data challenges. There is a lack of geo-temporal poverty data; this project will develop new methods to produce such data. Consequently, the aim of this project is to identify to what extent African communities are trapped in poverty and explain how competing development interventions alter these communities' prospects to free themselves from deprivation. To achieve this aim, the project will (i) develop machine learning algorithms to identify poverty traps from satellite images (e.g. NASA's Landsat mission) between 1980s to 2020; (ii) use these remote sensing derived poverty data to examine how World Bank versus Chinese development programs target and communities; (iii) investigate the extent to which such analysis can be used to draw causal conclusions about the impact of development pograms (iv) using this foundational work, scale up the results from (i) - (iii) to validate them and develop a theory of the varieties of poverty traps and targeting. Lastly, (iv) To produce a statistical package - PovertyMachine - that enables us, and other scholars, to produce poverty estimates from new images (i).

The project is a collaboration between Chalmers University of Technology and the Department of Sociology, University of Gothenburg. Accordingly, although the student will pursue a PhD in machine learning within computer science and engineering at Chalmers, this person expected to have an interest in social-scientific issues and interdisciplinary research.

Job description
The research assistant is expected to provide data-science support for the researchers in the project, focusing primarly to satisfying the project's first and third aims: “To develop machine learning and causal inference algorithms to identify poverty levels and poverty traps using satellite images, of African communities over time and space, on a quarterly basis, from the 1980s to 2020.” The role of the RA is primarly focused on (1) gathering census and survey data (2) assembling satellite image data from Google Earth Engine using javascript, Python (or R programming), and (3) support and conduct preliminary analyses using various deep-learning algorithms.

Contract terms
Temporary employment, 50-100 %, December 2020 - June 2021.

Your qualifications
Applicants must have a background in computer science, mathematics, signal processing, physics or related fields, and experience in machine learning. They must have obtained a Master's degree or a 4-year Bachelor's degree in one of these fields, or expect to complete that degree by the time the employment starts. Knowledge of Swedish is not a prerequisite for applying since English is our working language for research.

Chalmers continuously strives to be an attractive employer. Equality and diversity are substantial foundations in all activities at Chalmers.

Our offer to you
Chalmers offers a cultivating and inspiring working environment in the dynamic city of Gothenburg. 
Read more about working at Chalmers and our benefits for employees.

APPLY HERE

Application deadline: 13th November 2020

For questions, please contact:
Adel Daoud, GU, adel.daoud@sociology.gu.se
Fredrik Johansson, CSE DSAI, fredrik.johansson@chalmers.se, +46 073 591 7101

*** Chalmers declines to consider all offers of further announcement publishing or other types of support for the recruiting process in connection with this position. ***



Chalmers University of Technology conducts research and education in engineering sciences, architecture, technology-related mathematical sciences, natural and nautical sciences, working in close collaboration with industry and society. The strategy for scientific excellence focuses on our six Areas of Advance; Energy, Health Engineering, Information and Communication Technology, Materials Science, Production and Transport. The aim is to make an active contribution to a sustainable future using the basic sciences as a foundation and innovation and entrepreneurship as the central driving forces. Chalmers has around 11,000 students and 3,000 employees. New knowledge and improved technology have characterised Chalmers since its foundation in 1829, completely in accordance with the will of William Chalmers and his motto: Avancez!