Doctoral student in Image representations for class discovery

KTH

Application deadline

May 28, 2026



KTH Royal Institute of Technology, School of Electrical Engineering and Computer Science 

Project description

Third-cycle subject: Computer Science

The Division of Robotics, Perception and Learning has an open position for a doctoral student with a background and strong interest in computer vision and deep generative learning. The successful candidate will join a WASP funded project to learn better image representations, based on generative approaches, for out-of-distribution discovery and novel species discovery for fine-grained classification. We anticipate incorporating genomic measurements into the identification process. The algorithms developed will be application area independent, but a particular focus will be put on plankton species identification with the goal to build more robust classification and novel species identification systems.

You will be part of ongoing collaboration between the groups of Assoc Prof Josephine Sullivan at RPL, Prof Anders Andersson (Environmental Genomics) at the SciLife Lab and Bengt Karlson at SMHI. The PhD student will be part of WASP graduate school. Check out this article for details of scientific output from this collaboration “The ocean’s smallest creature is mapped“.

Supervision: Associate Professor Josephine Sullivan and Professor Anders Andersson are proposed to supervise the doctoral student. Decisions are made on admission

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
  • This project will require practical proficiency in deep learning. Thus demonstrated competency in deep learning programming libraries such as TensorFlow, PyTorch, or JAX is a must and experience with GPU-based experimentation and cluster computing (e.g., Docker, Slurm) a plus.

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

Selection

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
  • analyze and work with complex issues.

In the evaluation of candidates, an emphasis will be place on academic results, completed courses and demonstrated programming ability via completed project work. An earlier specialization in computer vision and/or machine learning is highly desirable and especially meritorious.

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

Target degree: Doctoral degree

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.

As a doctoral student, you are entitled to a workplace with many employee benefits and monthly salary according to KTH’s Doctoral student salary agreement. Read more about Doctoral studies (PhD) | KTH | Sweden.

Union representatives

Contact information for union representatives.

Doctoral Student’s network (Students’ union on KTH Royal Institute of Technology)

Contact information for PhD chapter.

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 include the following elements:

  • 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.
  • CV including your relevant professional experience and knowledge.
  • Representative publications or technical reports: For longer documents, please provide a summary (abstract) and a web link to the full text.

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

Other information

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

It may be the case that a position at KTH is classified as a security-sensitive role in accordance with the Protective Security Act (2018:585). If this applies to the specific position, a security clearance will be conducted for the applicant in accordance with the same law with the applicant’s consent. In such cases, a prerequisite for employment is that the applicant is approved following the security clearance.

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Learn more about our benefits and what it’s like to work and grow at KTH

Type of employmentTemporary position
Contract typeFull time
First day of employmentAccording to agreement 
SalaryMonthly salary according to KTH’s doctoral student salary agreement
Number of positions1
Full-time equivalent100%
CityStockholm
CountyStockholms län
CountrySweden
Reference numberPA-2026-1417
ContactJosephine Sullivan, sullivan@kth.se
Published07.May.2026 
Last application date28.May.2026

Last updated: 2026-05-07

Content Responsible: Anna Frejd(anna.frejd@scilifelab.se)