Summary:
KTH Royal Institute of Technology invites applications for a doctoral student position focused on image representations for class discovery. The project aims to develop generative approaches for better out-of-distribution discovery and novel species identification, particularly targeting plankton species. The candidate will collaborate with experts in environmental genomics and engage in an interdisciplinary research environment.
Doctoral Student in Image Representations for Class Discovery, KTH Royal Institute of TechnologyStockholm, Sweden
Designation:
Doctoral Student
Research Area:
- Computer Vision
- Deep Generative Learning
- Fine-grained Classification
- Environmental Genomics
Location:
KTH Royal Institute of Technology
Stockholm, Sweden
Eligibility/Qualification:
- Completed a second-cycle degree (master’s degree) or equivalent (240 higher education credits, including 60 second-cycle credits).
- Practical proficiency in deep learning (TensorFlow, PyTorch, or JAX).
- Experience with GPU-based experimentation and cluster computing (Docker, Slurm) is a plus.
- Mandatory English proficiency equivalent to English B/6.
Job Description:
- Join a WASP-funded project for developing robust classification systems.
- Collaborate on research involving genomic measurements to enhance species identification.
- Work under the supervision of leading academics in the field.
How to Apply:
- Submit your application through KTH’s recruitment system.
- Include the following documents:
- Copies of diplomas and grades from previous studies and language requirement certificates (translations required if not in English/Swedish).
- CV detailing relevant professional experience.
- Representative publications or technical reports (include abstracts and web links for longer documents).
It is the applicant’s responsibility to ensure the application is complete by the closing date.
Last Date to Apply:
May 28, 2026
For further information, please contact Josephine Sullivan at sullivan@kth.se.
