Summary
The KTH Royal Institute of Technology is seeking an outstanding postdoctoral researcher in computational biology to enhance the integration and modeling of large-scale microscopy data through modern machine learning approaches. The successful candidate will work within a highly interdisciplinary environment, focusing on uncovering conserved cellular state transitions and biological discovery.
Postdoc in Machine Learning for Bioimage-Based Profiling, Stockholm, Sweden
Designation
Postdoctoral Research Fellow
Job Details
| Field | Details |
|---|---|
| Research Area | Machine Learning, Computational Biology |
| Location | Stockholm, Sweden |
| Type of Employment | Temporary position, full-time |
| Contract Duration | Up to 2 years |
| Monthly Salary | Not Specified |
| Number of Positions | 1 |
| Full-time Equivalent | 100% |
Eligibility/Qualification
Requirements:
- A doctoral degree or an equivalent foreign degree.
- Significant research expertise in image-based profiling and computational biology methods for single-cell or tissue data.
- Extensive knowledge of relevant machine learning and AI techniques.
- Proven scientific excellence demonstrated by a strong publication record.
- Strong programming skills in Python or R and familiarity with high-performance computing.
Preferred Qualifications:
- Doctoral degree obtained within the last three years.
- Highly creative and collaborative researcher.
- Self-motivated with the ability to work independently.
- Interest in teaching and mentorship.
- Awareness of diversity and equal opportunity issues, particularly regarding gender equality.
Job Description
Cellular morphology reflects fundamental biological processes such as division, differentiation, stress response, and apoptosis. This project aims to determine whether shared biological structures can be recovered across heterogeneous datasets using representation learning and generative modeling methods. The position involves leading independent research projects at the intersection of machine learning and biology, with an emphasis on method development, large-scale data integration, and biological discovery.
How to Apply
To apply for the position, please log into KTH’s recruitment system and ensure your application includes:
- CV detailing relevant professional experience and knowledge.
- Copies of diplomas and grades from previous university studies, translated into English or Swedish if necessary.
- A brief account (max two pages) explaining your research interests, academic background, and future goals.
Complete applications must be received no later than midnight CET/CEST on the last application date.
Last Date for Application
17 April 2026
For further information, please contact:
- Gisele Miranda
Email: gmirand@kth.se
