Assistant Professor Artificial intelligence for early warning in data sparse environments
Updated: 29 Sep 2023
You will develop a research direction and educational profile within the ambitions of the ITC Faculty Geo-Information Science and Earth Observation, University of Twente, and the Netherlands sector of Earth and Environmental Sciences. You will contribute to our MSc programmes, co-supervise graduate students and work with our E-Learning Specialists to develop online educational materials.
You will take responsibility for coordination and management tasks and take an active approach towards strengthening our national network, particularly in the broader Earth and Environmental Sciences domain in the Netherlands.
Building operational early warning systems that accurately and timely inform governments, organizations, and communities about potential natural hazard (hydro-meteorological, geomorphological, etc.) threats is a challenge. This challenge exists in data-rich contexts, where scientists can rely on large networks of in-situ measurements or remotely sensed information that provides data in near-real time. In the majority world, often availability and access to near-real-time data are lacking, particularly for in-situ observations, making the challenge even bigger. In such cases, the use of intelligent systems is fundamental to reduce spatiotemporal biases due to poor data availability, as well as to integrate new data sources from remote sensing with the limited in-situ observations one may get access to. For large regions, these problems become highly dimensional. This calls for interdisciplinary approaches, particularly for physics- and data-driven architectures that are flexible enough to be adapted to space-time predictive modelling, image processing, time series analyses, classification and regression tasks tailored toward utmosts. These techniques are part of modern machine/deep learning toolsets, which you will use, develop, and adapt to address priorities in line with Sustainable Development Goals and specifically to SDG 11.5: Reduce the Adverse Effects of Natural Disasters.
- A PhD degree in computer science, software engineering, data science or statistics with an interest in natural hazards or a PhD degree in geosciences with an interest in artificial intelligence. If not finished yet, your PhD should be close to completion
- Interest in translating your research into practical applications and collaborating with partners
- Embrace Open Science and FAIR data principles
- Passion for education, supervising graduate students and emerging researchers, and the ability to develop high-quality educational materials
- Interest in contributing to the capacity development mission of ITC and willingness to undertake international travel to low and middle-income countries
- Thrive in a multi-cultural academic environment, and like working in a range of international and interdisciplinary contexts
- Excellent command of English. Knowledge of, and/or willingness to learn Dutch is an advantage.
- A team-work mentality; you enjoy collaborating to develop high-quality research outputs
- An inspiring multidisciplinary, international and academic environment. The university offers a dynamic ecosystem with enthusiastic colleagues in which internationalization is an important part of the strategic agenda
- Position for initially one year (full-time), after which your position can become permanent, subject to a successful evaluation
- Gross monthly salary between € 4,332.- and € 4,786.- (depending on experience and qualifications, job profile Assistant Professor, level 2). This is the maximum start salary with growth opportunities
- A holiday allowance of 8% of the gross annual salary and a year-end bonus of 8.3%
- Excellent support for professional and personal development
- A solid pension scheme
- A total of 41 holiday days in case of full-time employment
- Costs for moving to Enschede may be reimbursed
40 hours per week