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PhD student position in Deep Learning for Predicting Poverty from Satellite Images


The Data Science and AI division at the Department of Computer Science and Engineering is recruiting a PhD student for a project in Observatory of Poverty, within the research project Observatory of Poverty, funded by the Swedish Research Council (SRC).

Information about the research 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 tackle the following objectives:

Obj1: To train learning algorithms to identify poverty from satellite images, of African communities over time and space, quarterly, from 1984 to 2020.
Obj2: To examine how World Bank (WB) development programs versus Chinese programs, select African communities, and how these affect communities’ chances of breaking the cycle of deprivation (using the data of Obj1).
Obj3: To develop theories of the varieties of poverty traps by examining the extent to which these traps lurk in different social contexts that shape both local governance and public-service provisioning, and how these contexts may be more or less important for Chinese- or WB-styled projects.
Obj4: To create a statistical package—PovertyMachine—that enables us, and other scholars, to produce poverty estimates (Obj1) and conduct comparative program evaluations (Obj2 and Obj3).

The doctoral student is expected to pursue research mainly related to the project’s first and fourth objectives.

The project is a collaboration between Chalmers University of Technology, the Department of Sociology, University of Gothenburg, and the Institute for Analytical Sociology, Linköping University. 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.

Major responsibilities
Your main responsibility as a PhD student is to pursue your doctoral studies within the framework of the outlined research project. You will be enrolled in a graduate program in the Department of Computer Science and Engineering. You are expected to develop your own ideas and communicate scientific results orally as well as in written form. In addition, the position includes 20% departmental work, mostly as a teaching assistant in Chalmers' undergraduate and masters-level courses or performing other departmental tasks.

Position summary
Full-time temporary employment. The position is limited to a maximum of five years.

To qualify as a PhD student, you must have a master's-level degree, or a four-year bachelor's degree, corresponding to at least 240 higher education credits in computer science, mathematics, signal processing, physics or related field at the time of start and experience in machine learning. The position requires sound verbal and written communication skills in English. Knowledge of Swedish is not a prerequisite for applying since English is our working language.

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. Chalmers offers Swedish courses.

Application procedure
The application should be marked with Ref 20210166 and written in English. The application should be sent electronically and be attached as pdf-files, as below:

CV: (Please name the document: CV, Family name, Ref. number)
• CV
• Other, for example previous employments or leadership qualifications and positions of trust.
• Two references that we can contact.

Personal letter: (Please name the document as: Personal letter, Family name, Ref. number)
1-3 pages where you:
• Introduce yourself
• Describe your previous experience of relevance for the position (e.g. education, thesis work and, if applicable, any other research activities)
• Describe your future goals and future research focus

Other documents:
• Copies of bachelor and/or master’s thesis.
• Attested copies and transcripts of completed education, grades and other certificates, e.g. TOEFL test results.

Please use the button at the foot of the page to reach the application form. The files may be compressed (zipped).

Application deadline: 1st May, 2021

For questions, please contact:
Adel Daoud, CSE DSAI
Fredrik Johansson, CSE DSAI,

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

Information about the department
The Department of Computer Science and Engineering is a joint department at Chalmers University of Technology and the University of Gothenburg, with activities on two campuses in the city of Gothenburg. The department has around 270 employees from over 30 countries. Our research has a wide span, from theoretical foundations to applied systems development. We provide high quality education at Bachelor's, Master's and graduate levels, offering over 120 courses each year. We also have extensive national and international collaborations with academia, industry and society.

Our aim is to actively improve our gender balance in both our department and division. We therefore strongly encourage female applicants for our positions. As an employee at Chalmers and the Department of Computer Science and Engineering, you are given the opportunity to contribute to our active work within the field of equality and diversity. We are working broadly with equality projects, for example the GENIE Initiative on gender equality for excellence. For more information, visit our website. 

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!





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