Doctoral Candidate Spatial statistics for integrating IoT field sensor data and remote sensing data for nature-inclusive solutions in tree crop diseases
Doctoral Candidate
Spatial statistics for integrating IoT field sensor data and remote sensing data
for nature-inclusive solutions in tree crop diseases
The University of Twente, Faculty ITC, wishes to increase the number of women in the faculty to have a more balanced staff profile. During all phases of the selection process, we will therefore prioritize selecting women who fit the profile.
Your challenge
The Dutch government, through the Ministry of Education, Culture and Science, has responded to the current global environmental challenges by establishing sector plan positions in critical scientific domains. At the Department of Environmental Resources, one of our activities is to address these challenges by developing and applying Geostatistical models for bridging knowledge gaps, data scarcity and uncertainty gaps, and governance gaps related to monitoring the environment on which humans depend.
A part of this is spatial statistics of sensor data integration for nature-inclusive solutions for monitoring stress and diseases of tree crops. Tree crops like cocoa, apart from their direct economic functions for smallholder farmers, sit at the intersection of many beneficial ecological functions (including carbon sequestration and cultural identity). However, these functions are threatened by environmental stressors and diseases such as Cocoa Swollen Shoot Virus (CSSV) disease, which depend on the complex web of interactions between and within above-ground and below-ground biotic and abiotic factors. The prevailing data and methodological gaps that have perpetuated knowledge gaps in the spatial and spatiotemporal patterns of tree disease, and the widened governance gaps of farms, have motivated this topic.
You will develop spatial statistical methods to integrate ground-based IoT sensor data, remote sensing data, and in-situ data for mapping the spatial trends of cocoa diseases. You will be involved in setting up an IoT sensor network in cocoa farms in Ghana. You are expected to address data integration challenges, including (1) spatial misalignment of networks, (2) temporal misalignments of observations, (2) probabilistic or likelihood misalignments, and (3) data quality issues, such as uncertainties in measurements, sparsity of network coverage resulting in small N, missing data resulting from malfunction of sensors, and outliers. For the purposes of evaluating model transferability, you will make a comparison with other economically important tree crops in food forests in the Netherlands. You will design a measurement setup for cocoa trees and review the wide range of applications of IoT sensors, their uncertainties, and the observable variables above and below ground that are important for predicting tree crop diseases and stresses. You will also explore simulation scenarios to evaluate the impact of indigenous and formal farming management practices on plant diseases.
Information and application
For more information, you may contact Dr Ir Frank Osei (email: f.b.osei@utwente.nl) or Prof Dr Wieteke Willemen (email: l.l.willemen@utwente.nl). You are also invited to visit our homepage.
Please submit your application before October 31, 2026, including:
- A motivation letter (one page maximum) emphasising your specific interests, qualifications, and motivation for this position
- A Curriculum Vitae (including a list of all courses attended, grades obtained, the names and contact information of two references, and – if applicable – a publication list)
- A written example of your scientific work, such as an MSc thesis, a recent individual report, or an article
- First-round (online) interviews are scheduled in the second half of November. A (possible) second-round interview might take place in early December.
- Applications that do not include the above-mentioned information will not be considered.
Screening is part of the selection procedure.
For questions about working and living in the Netherlands, please consult the official website of the Dutch Government or the Expat Center East Netherlands website.
About the department
Environmental Resources are crucial to maintaining the well-being of societies. Sustainable management of these natural resources balances the needs of people and the environment. It avoids the depletion, degradation, and destruction of ecosystems, prevents biodiversity loss and soil erosion, and mitigates the impacts of climate change. Our research, education, and partnerships empower society to effectively use insights from geo-information and Earth observation technologies to sustainably manage the environment. The outcome is an increased understanding of the processes that affect the availability, stability, quality, and sustainability of natural resources, enabling their preservation, sustainable use, development, or restoration. Our academic staff, PhD candidates, and MSc students focus on developing both the means and the measurements essential for monitoring
About the organisation
The Faculty of Geo-Information Science and Earth Observation (ITC) provides international postgraduate education, research and project services in the field of geo-information science and earth observation. Our mission is capacity development, where we apply, share and facilitate the effective use of geo-information and earth observation knowledge and tools for tackling global wicked problems. Our purpose is to enable our many partners around the world to track and trace the impact – and the shifting causes and frontiers – of today’s global challenges. Our vision is of a world in which researchers, educators, and students collaborate across disciplinary and geographic divides with governmental and non-governmental organisations, institutes, businesses, and local populations to surmount today’s complex global challenges and to contribute to sustainable, fair, and digital societies.
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