EngD position: AI for Underground Infrastructure Detection and Characterisation

Karlstad University; Enschede; On-site; EUR 32,000 - 39,000; Full time

Benefits offered by this job

Two-year EngD position

Pension and health care benefits

Tailor-made post-master programme (40%

design project (60%)

Gross monthly salary of €3173

Annual holiday allowance 8% of gross,

Year-end bonus 8.3%

Mentorship for professional/personal成长

EngD degree and KIVI registration

Job summary

University of Twente seeks an EngD candidate to develop AI for automatic detection and characterization of underground infrastructure in GPR radargrams. The role combines geospatial sensing, AI, and practical measurement practices within the ZoARG|ReDUCE programme.

You will work across civil engineering, AES, and industry partners to validate models and translate findings into safe excavation practices.

Qualifications

• Master’s degree or equivalent in a related field is required.
• Experience with machine learning, data analytics, or computer vision techniques.
• Programming in Python and familiarity with ML frameworks (PyTorch, TensorFlow).
• Interest in geospatial data, remote sensing, subsurface sensing, or utility mapping.
• Strong analytical and problem-solving skills; able to work independently and with partners.

Responsibilities

• Analyse existing GPR interpretation methods and ML techniques.
• Explore AI approaches for automated utility characterization.
• Prepare and manage large GPR datasets collected at UT FieldLab.
• Design, train, and validate ML models for interpreting radargrams.
• Compare models with literature and commercial software.
• Collaborate with infrastructure owners, contractors, and researchers.
• Report findings and translate results into practical recommendations.

Skills

Machine learning experience

Data analytics

Geospatial interests

Analytical thinking

English communication

Education

Master’s degree or equivalent (Civil Engineering, Geomatics, CS, Data Science)

Tools

Python

PyTorch

TensorFlow

Geospatial software

Job description

EngD position: AI for Underground Infrastructure Detection and Characterisation

Looking for a job that matters? Join the university of technology that puts people first – and shape new opportunities both for yourself and for ou...

In this EngD project, you will develop an AI model that automatically detects underground infrastructure in GPR radargrams and estimates its depth. The project builds on the growing availability of high-quality GPR data collected at the University of Twente’s Utility Mapping Site (UMS), a unique test environment for utility mapping technologies.

Current machine learning models and their training data are limited in size, comprehensiveness, and realism – resulting in partial automation with limited performance. This constrains their usefulness in real-world conditions. Your challenge is to develop and validate machine learning models using systematically collected and accurately annotated GPR datasets. By combining geospatial data, subsurface sensing, and AI, you will contribute to the next generation of utility mapping technologies and support safer excavation practices.

This project is part of the ZoARG|ReDUCE programme, a collaborative initiative aimed at minimizing excavation damage to underground infrastructure in the Netherlands. You will work within a multidisciplinary environment that includes:

• The University of Twente’s Departments of Civil Engineering and Management (CEM) and Applied Earth Sciences (AES)
• The Utility Mapping Site (UMS) at the UT FieldLab
• Industry collaborators involved in the ZoARG programme

What you will do

• Analyse existing GPR interpretation methods, machine learning techniques, and relevant software tools
• Explore and evaluate AI approaches for automated utility characterization
• Prepare, preprocess, and manage large GPR datasets collected at the Utility Mapping Site
• Design, develop, train, and validate machine learning models for interpreting GPR radargrams
• Compare developed models with existing approaches reported in literature and commercial software solutions
• Work in close partnership with infrastructure owners, contractors, technology providers, and researchers engaged in the ZoARG programme
• Report findings and translate results into practical recommendations for measurement practice and technology evaluation

Your profile

• A Master’s degree or equivalent experience in Civil Engineering, Geomatics, Computer Science, Data Science, or a related field
• Experience with machine learning, data analytics, or computer vision techniques
• Programming experience in Python and familiarity with machine learning frameworks such as PyTorch, TensorFlow, or similar tools
• Curiosity about geospatial data, remote sensing, subsurface sensing, or utility mapping applications;
• Strong analytical and problem-solving skills
• The ability to work independently and collaborate effectively with academic and industrial partners
• Excellent communication skills and proficiency in English

Our offer

• Two-year full-time EngD position, where scientific and research domains are combined optimally with education and practical implementation of innovative design
• Full status as an employee at the UT, including pension and health care benefits
• A tailor-made post-master build programme that has an educational component (40%) as well as a design project (60%)
• A gross monthly salary of €3173
• An annual holiday allowance of 8% of the gross annual salary, and an annual year-end bonus of 8.3%
• Minimum of 29 holidays per year in case of full-time employment
• A work environment on a green and lively campus with (free access) to sports and leisure facilities
• Mentorship that supports your professional and personal growth
• Upon finishing the programme, you will be awarded a certified degree. You can use the academic title EngD and register as a Technological Designer in the Dutch registry of the Royal Institution of Engineers in the Netherlands (KIVI).

About the organisation

At the Faculty of Engineering Technology (ET), we work on engineering for impact: developing smart, sustainable, human-centred and technological solutions for societal challenges. We connect fundamental education, research and practice across five core domains: Asset & Maintenance engineering, Intelligent Manufacturing Systems, Personalised Health Technology, Resilience Engineering, and Sustainable Production, Energy and Resources.

We work on education and research in mechanical engineering, civil engineering and industrial design engineering. Together, we learn by making, creating, and innovating, addressing challenges in a solution-oriented way. Quality, connection and inclusivity are the foundation of our culture.

In our open community, students, researchers and staff collaborate with industrial and societal partners. This enables us to develop insights, applications and solutions that add value to society.

Job details

Title

EngD position: AI for Underground Infrastructure Detection and Characterisation

Published

2026-09-18