30%-40%, Zurich, fixed-term
City growth is something that happens in high-rise as much as horizontally. We are measuring the evolving floor space density in Chinese urban areas over the last couple of decades. Our goal is large scale time-series data on buildup in all Chinese cities for further research in urban economics. To achieve this we employ deep learning algorithms on various satellite imagery sources. The following link leads to a first milestone.
You will build up a large library of (mainly optical) satellite imagery and build a pipeline to preprocess it to the extent that we can feed it into a predicting model.
- Data Processing: This includes using the Planet-API and Google Earth Engine.
- Programming: The candidate should be able to understand existing codebase like (Gitlab ) and document the programming progress in git.
- Data Evaluation: Analyzing inputs and outputs of our model may also be part of the position.
- Paper Writing: The prospective candidate is expected to support paper writing of the team. We expect the candidate to cope well with deadlines.
- Interdisciplinary Team: In weekly meetings, we discuss the progress of the project and brainstorm the next steps. We have a friendly work environment where bringing in own ideas is encouraged.
- Possible Extension: Spinoff-Master Thesis are also welcome.
The prospective candidate is expected to support paper writing of the team. We expect the candidate to cope well with deadlines.
- Python and GIS
- Knowlege of remote sensing methods and satellite imagery handling
- Ability to effectively manage substantial volumes of data (over 500GB)
- Experience with remote sensing/satellite imagery analysis (google earth engine or similar)
- Experience with CNN (pytorch, tensorflow or similar) is a plus
- Chinese is a plus
You can start as soon as possible. We encourage students from study programs with a focus on remote sensing, GIS, and urban planning to apply. You must be enrolled at a Swiss University and must be willing to work 15h/week on average during the semester. It is possible to work more during the semester breaks (up to 40 hours possible). We handle working time flexibly such that you can take time to study for exams or fulfil other obligations for your studies while coordinating with the team when tasks need to be completed. Ideally, we are looking for individuals who can stay employed as a student assistant for at least one year (e.g., while taking courses for their Bachelor's or Master's degree), possibly longer.
- An interdisciplinary team with good support and a friendly learning environment.
- A possibility to work onsite/remotely
- Standard ETH student RA salary
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We look forward to receiving your online application .
Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.
Further information about CAE can be found on our website . Questions regarding the position should be directed to Sebastiano Papini, email: firstname.lastname@example.org
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