PhD in Spatial Statistics for IoT, Field Sensors and Remote Sensing

Laplace Expert Ltd; Netherlands; Remoto; EUR 36.000 - 45.000; Tempo pieno

Descrizione del lavoro

University of Twente in the Netherlands is recruiting a PhD candidate to develop spatial-statistical methods that integrate IoT field sensors and remote sensing for nature-inclusive management of tree-crop diseases.

The project focuses on integrating field observations, IoT sensors, and remote sensing to monitor cocoa diseases and transfer methods to nature-inclusive systems in the Netherlands. Four-year, full-time doctoral position with competitive funding.

Competenze

• MSc in geo-information science, Earth observation, geospatial data science or related field.
• Experience with spatial or spatiotemporal modelling and spatial statistics.
• Ability to integrate multi-temporal and multi-spatial datasets.
• Experience with machine learning is advantageous.

Mansioni

• Develop spatial-statistical methods integrating IoT field sensors and remote sensing.
• Apply methods to monitor cocoa disease and support nature-inclusive agriculture.
• Collaborate on data fusion from heterogeneous sources.

Conoscenze

Spatial statistics

Spatiotemporal modelling

IoT sensor integration

Machine learning

Python

R

Remote sensing

Formazione

MSc in geo-information science or related field

Descrizione del lavoro

PhD in Spatial Statistics for IoT, Field Sensors and Remote Sensing

University of Twente · Faculty of Geo-Information Science and Earth Observation (ITC)

Netherlands

Apply by 30 Oct 2026

About This Opportunity

The University of Twente is recruiting a doctoral candidate to develop spatial-statistical methods that integrate IoT field sensors and remote sensing for nature-inclusive management of tree-crop diseases. Applications close on 30 October 2026 at 23:59 Europe/Amsterdam.

The project develops spatial and spatiotemporal statistical methods to integrate field observations, IoT sensors, airborne or satellite remote sensing and other heterogeneous data for monitoring cocoa disease in Ghana and transferring methods to nature-inclusive systems in the Netherlands.

spatial statistics remote sensing IoT sensors cocoa disease nature-inclusive agriculture

Level PhD

Attendance Field-based

Time Commitment Full-time

Duration 4 years

Reference Code 2608

Field Spatial Statistics and Remote Sensing for Tree Crop Disease

Organization Type University

Funding & Compensation

Amount EUR 3204-4051 / Per Month

Funding Type Salary

Funding Status Paid

Period Per Month

Requirements

Education

Applicants should hold an MSc in geo-information science, Earth observation, geospatial data science or a closely related field.

Experience

Experience with spatial or spatiotemporal modelling, spatial statistics and/or machine learning is expected, together with the ability to integrate multi-temporal and multi-spatial datasets.

Technical Skills

• Spatial statistics
• Spatiotemporal modelling
• Remote sensing
• IoT sensor integration
• Python
• R
• Machine learning