Phd Thesis “Applying Satellite-Based Remote Sensing to Transportation Infrastructure Monitoring”

AIT Austrian Institute of Technology

Town of Vienna (WI)

Sur place

USD 38 000 - 46 000

Plein temps

14 jours+

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Avantages offerts par ce poste

Home office options
PhD community access
Flexible working models

Résumé du poste

The AIT Austrian Institute of Technology invites applications for a PhD thesis at our Vienna location, within the Center for Transport Technologies. The project focuses on applying satellite-based remote sensing to transportation infrastructure monitoring across roads, railways, and bridges.

You will conduct independent research, select satellite missions, develop and validate methodologies, and publish results in peer-reviewed journals while collaborating with international partners.

Qualifications

  • Master's degree in Civil Engineering, Remote Sensing, Geodesy and Geoinformatics, Aerospace Engineering, Data Science, or a related field.
  • Solid programming skills in Python, MATLAB, C++, or other programming languages.
  • Experience with remote sensing data (e.g. InSAR, optical satellite) and processing large datasets is an advantage.
  • Interest in reading and writing scientific publications and application-oriented research.
  • Excellent German and English language skills and strong presentation abilities.

Responsabilités

  • Conduct independent scientific research in satellite-based transportation infrastructure monitoring.
  • Identify suitable satellite missions and remote sensing datasets (e.g., SAR, InSAR, optical, multispectral).
  • Develop innovative methodologies for using remote sensing data in infrastructure monitoring.
  • Implement methodologies in a pilot study and perform validation analyses.
  • Evaluate analytical methods for accuracy, robustness, and practical applicability.
  • Present research findings at scientific conferences and publish in peer-reviewed journals.
  • Gain experience in an interdisciplinary research field spanning civil engineering, geoinformatics, aerospace, and data science.
  • Expand scientific and professional networks for a future career in research or industry.

Connaissances

Python
MATLAB
C++

Formation

Master's degree in Civil Engineering, Remote Sensing, Geodesy and Geoinformatics, Aerospace Engineering, Data Science, or related field

Description du poste

The AIT Austrian Institute of Technology is Austria's largest Research and Technology Organisation (RTO). We aim to transform scientific excellence into innovation with impact. Together with our partners, we develop technologies and solutions for a sustainable, resilient, and digitalized future, strengthening Europe’s competitiveness and technological sovereignty. Our international teams combine cutting-edge research with strong implementation expertise to create measurable value for industry and society.

Our Center for Transport Technologies invites applications for a PhD thesis at our location in Vienna. Within the Competence Unit Transportation Infrastructure Technologies, our research team, specialising in structural health monitoring, structural dynamics, and bridge engineering, works closely with industrial partners. Our research covers the development of innovative measurement and monitoring methods, including fiber-optic sensing as well as video- and satellite-based technologies, through to measurement-based structural assessment and life cycle assessment. We focus on both newly constructed and existing infrastructure, including transportation infrastructure, civil engineering structures, and buildings.

The PhD project focuses on the development of novel applications for the use of earth observation data in transportation infrastructure monitoring. The research covers various modes of transport (incl. roads, railways, and waterways) as well as their associated engineering structures (bridges, retaining walls, noise barriers, and hydraulic structures). A wide range of remote sensing data may be used, including radar, optical, and thermal data, with a particular focus on the European Copernicus Sentinel satellite missions (e.g. Sentinel-1 to Sentinel-6). The project is embedded in several national and international research collaborations with Austrian and international partners in this field.

Phd Thesis "Applying Satellite-Based Remote Sensing to Transportation Infrastructure Monitoring"
CENTER FOR TRANSPORT TECHNOLOGIES
  • You will conduct independent scientific research in the field of satellite-based transportation infrastructure monitoring, for example by developing innovative approaches for detecting deformations, damage, settlements, or condition changes in road, railway, or bridge infrastructure.
  • Together with our experts, you will identify suitable satellite missions and remote sensing datasets such as SAR, InSAR, optical, or multispectral data and evaluate their suitability for specific monitoring applications.
  • You will develop an innovative methodological approach for the use of remote sensing data in infrastructure monitoring, including data preparation, processing, time series analysis, accuracy assessment, and the potential integration with existing infrastructure or asset management data.
  • You will implement the developed methodology within a pilot study and perform validation analyses as well as accuracy comparisons between different data sources and/or processing approaches.
  • You will evaluate and validate different analytical methods with regard to their accuracy, robustness, and practical applicability, for example by comparing them with terrestrial reference data.
  • You will present your research findings at scientific conferences and publish your results in national and international peer-reviewed journals as part of your doctoral research.
  • You will gain experience in a highly interdisciplinary research field with applications spanning civil engineering, geoinformatics, aerospace, transportation engineering, data science, and asset management.
  • You will expand your scientific and professional network while developing the expertise required for a future career in research, industry, or public infrastructure management.

Your qualifications as an Ingenious Partner:

  • A completed or soon-to-be-completed Master's degree (MSc) in Civil Engineering, Remote Sensing, Geodesy and Geoinformatics, Aerospace Engineering, Data Science, or a related field.
  • Solid programming skills in Python, MATLAB, C++, or other programming languages.
  • Experience working with remote sensing data (e.g. InSAR, optical satellite) and processing large datasets is an advantage.
  • An interest in reading and writing scientific publications, combined with enthusiasm for application-oriented industrial research.
  • A high level of commitment and a collaborative mindset.
  • Excellent German and English language skills, along with strong presentation abilities.

Details:

  • Duration: Approximately 3 years.
  • Start date: Ideally from 10.2026, with flexibility regarding the exact starting date.
  • Workplace: You will carry out your research project together with our team at the AIT in Vienna.
  • Coursework: If required by the doctoral programme, you may attend university courses and complete the corresponding examinations.
  • Supervision: You will be jointly supervised by a professor or lecturer from the selected university and by our experienced researchers and engineers from the Center for Transport Technologies.

What to expect:

  • A gross annual salary of EUR 37.478 for 30 hours per week.
  • In addition to numerous events, seminars, networking opportunities, flexible working models (incl. Home-Office possibilities) and other company benefits, you will be part of the AIT-PhD-Community with approx. 150 international PhD students.

At AIT, we create an inclusive and family-friendly working environment that promotes equal opportunities and actively strengthens diversity across our workforce and in leadership positions. Among other initiatives, we are committed to increasing the proportion of women in our company and therefore particularly welcome applications from female applicants.

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