School of Architecture and Built Environment at KTH

Project description

Third-cycle subject: Geodesy and Geoinformatics

We are excited to announce a new PhD position in "Foundation Models for Earth Observation Big Data" This research opportunity will center on the development of cutting-edge self-supervised models and strategies aimed at harnessing the vast potential of multi-modal, multi-temporal, and multi-resolution satellite imagery. The focus of this doctoral research will be on creating innovative models that not only capture complex spatiotemporal patterns but also enhance various downstream tasks, including change detection, segmentation, and regression. If you are passionate about advancing the field of Earth observation with artificial intelligence and have a strong background in machine learning, computer vision, or remote sensing, we encourage you to apply and be part of this journey towards revolutionizing Earth observation big data analysis.

Supervision: Professor Andrea Nascetti and Professor Yifang Ban is proposed to supervise the doctoral student. Decisions are made on admission

What we offer

Admission requirements

To be admitted to postgraduate education (Chapter 7, 39 § Swedish Higher Education Ordinance), the applicant must have basic eligibility in accordance with either of the following:

  • passed a second cycle degree (for example a master's degree), or
  • completed course requirements of at least 240 higher education credits, of which at least 60 second-cycle higher education credits, or
  • acquired, in some other way within or outside the country, substantially equivalent knowledge

In addition to the above, there is also a mandatory requirement for English equivalent to English B/6, read more here


In order to succeed as a doctoral student at KTH you need to be goal oriented and persevering in your work. During the selection process, candidates will be assessed upon their ability to:

  • independently pursue his or her work
  • collaborate with others,
  • have a professional approach and
  • analyse and work with complex issues.
  • Master's Degree in Geomatics, Computer Science, Electrical Engineering, or related disciplines in natural sciences and engineering.
  • Strong proficiency in image analysis, computer vision, pattern recognition, machine learning/deep learning, along with solid background in data science.
  • Prior experience with self-supervised models is a valuable asset.
  • Proficient coding skills in widely used scientific programming languages, including Python, C++, and Matlab.
  • Excellent ability to read and write scientific English and fluent spoken English since it is required in work.

After the qualification requirements, great emphasis will be placed on personal competency.

Target degree: Doctoral exam

Information regarding admission and employment

Only those admitted to postgraduate education may be employed as a doctoral student. The total length of employment may not be longer than what corresponds to full-time doctoral education in four years ' time. An employed doctoral student can, to a limited extent (maximum 20%), perform certain tasks within their role, e.g. training and administration. A new position as a doctoral student is for a maximum of one year, and then the employment may be renewed for a maximum of two years at a time. In the case of studies that are to be completed with a licentiate degree, the total period of employment may not be longer than what corresponds to full-time doctoral education for two years.

Union representatives

You will find contact information for union representatives on KTH's website.

Doctoral section (Students’ union on KTH Royal Institute of Technology)

You will find contact information for doctoral section on the section's website.

To apply for the position

Apply for the position and admission through KTH's recruitment system. It is the applicant’s responsibility to ensure that the application is complete in accordance with the instructions in the advertisement.

Applications must be received at the last closing date at midnight, CET/CEST (Central European Time/Central European Summer Time).

Applications must include the following elements:

  • CV including your relevant professional experience and knowledge.
  • Application letter with a brief description of why you want to pursue research studies, about what your academic interests are and how they relate to your previous studies and future goals. (Maximum 2 pages long)
  • Copies of diplomas and grades from previous university studies and certificates of fulfilled language requirements (see above). Translations into English or Swedish if the original document is not issued in one of these languages.Copies of originals must be certified.
  • Representative publications or technical reports. For longer documents, please provide a summary (abstract) and a web link to the full text.

Other information

The service may include security-sensitive activities. To become authorized, you therefore need to pass a security check.

Striving towards gender equality, diversity and equal conditions is both a question of quality for KTH and a given part of our values.

For information about processing of personal data in the recruitment process please read here.

We firmly decline all contact with staffing and recruitment agencies and job ad salespersons.

Disclaimer: In case of discrepancy between the Swedish original and the English translation of the job announcement, the Swedish version takes precedence.


Type of employment Temporary position
Contract type Full time
First day of employment According to the agreement
Salary Monthly salary according to KTH's doctoral student salary agreement
Number of positions 1
Full-time equivalent 100%
City Stockholm
County Stockholms län
Country Sweden
Reference number A-2023-2647
  • Andrea Nascetti,
  • Yifang Ban,
Published 09.Nov.2023
Last application date 15.Dec.2023 11:59 PM CET

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