You cannot apply for this job anymore (deadline was 29 Nov 2022).
Browse the current job offers or choose an item in the top navigation above.
The vacancy is within the scope of the 'SPACE4ALL: Mapping climate vulnerabilities of slums by combining citizen science and earth observation technology' project. The project is funded by the national research foundation NWO Open Competition Domain Science and aims to unravel the climate vulnerability of slum communities in six larger and secondary cities located in Ghana, Kenya and Nigeria by combining CS, EO data and AI methods.
You have to carry out research on a multidisciplinary project involving Citizen Science, Earth Observation and Artificial Intelligence (AI) for mapping climate vulnerabilities of slums. The main research objectives of this PhD position are to (1) implement a user-friendly Citizen Science (CS)-based application dedicated to collecting data related to the location, physical and socio-economic conditions of slums from Ghana, Kenya and Nigeria; (2) design, test and implement a novel and well-documented workflow that integrates Earth Observation (EO) and CS data for training transferable deep learning models for slum mapping and (3) identify the climate vulnerability hotspots of the mapped slums.
You will work closely with another PhD candidate who will develop a vulnerability model using AI, EO and CS data collected in the same slum areas. All research outcomes (collected data, developed workflows, CS application etc.) will be open-access to stimulate cross-disciplinary research.
University of Twente (UT)
- An MSc in Geoinformatics and/or Earth Observation
- Experience in machine learning and advanced programming skills (preferably in Python)
- Prior field data collection experience, optimally including citizen data collection methods
- Prior experience in conducting research in African countries with a focus on urban areas is a plus
- Able to do independent research and field data collection in slum communities in several African cities
- Good communication skills and a strong interest in operating at the crossroads of different disciplines
- Proficiency in written and spoken English
Conditions of employment
- An inspiring and challenging international environment
- Fulltime employment for 4 years
- Gross monthly salary of € 2,541.- in the first year and increases to € 3,247.- in the fourth year
- A holiday allowance of 8% of the gross annual salary and a year-end bonus of 8.3%
- Excellent support for research and facilities for professional and personal development
- A solid pension scheme
- A total of 41 holiday days in case of fulltime employment
The Department of Earth Observation Science (EOS) is engaged in education, research, and capacity building on earth observation, image analysis, and geo-health. The department develops and applies methods for the extraction of large-scale geo-information from, satellite, airborne and terrestrial sensors. The expertise of the department covers spatial statistics, image analysis, machine learning, deep learning, monitoring, and data integration. Geo-health relates the dynamics of diseases to the geo context. This is done by modeling the spread of diseases and their explanatory variables and includes understanding the emergence of diseases at various scales.