The Faculty of Geo-Information Science and Earth Observation (ITC) works in a variety of application domains in which voluminous geospatial data sources are fundamentally important to assess and monitor, manage, model and predict key change processes that take place in the Earth system. The faculty’s research and education focus on the professional and responsible use of Earth observation data and spatial information in combination with modern data handling systems. For these reasons, we are building a Big GeoData Science Lab for which are hiring new staff.
ITC aims to remain the global player in capacity development in advanced geospatial applications and is developing a reference curriculum in geospatial data science. This position is a key element in that effort. You have knowledge of geospatial data organization, machine learning techniques in data analysis, and the computational infrastructure required to make it work. You feel at home in a multi- and trans-disciplinary setting, and understand the role you can play in a team. You will complement and expand existing expertise in the faculty. You will aim to understand ongoing research projects, contribute with geospatial data science expertise and help build an educational curriculum. ITC aims to design a coordinated strategy in this scientific field to make its research and project activities future-proof, and generate educational spin-off. Thus, you will help steer and contribute to the development of a community of practice in our network on geospatial data science.
Various of ITC’s scientific departments are already engaged in work that has big data science dimensions. Such work primarily has a research orientation, but big geodata and data science are also becoming established in our educational programs, and more and more also in projects with external partners. Depending on application, purpose and audience data-intensive projects with large spatiotemporal data sets must make many choices, specifically in data preparation and analytical methods, in hardware/software platforms to use, and in the techniques to disseminate results. This diversity of choices is worthy of study itself. All these developments require vision and experience, understanding of the state-of-the-art and trends in cloud computing, and machine learning.
This position has a strong scientific orientation, operates at the assistant professor level, and focuses on shaping ITC’s capabilities in the field by seeking synergies across departments and applications. You liaise with staff, support their work, and aim to solidify their expertise as institutional knowledge. You contribute to papers, and on projects in the Global South.