Summary
Karolinska Institutet is inviting applications for a PhD student position in the Cancer Proteomics Mass Spectrometry research group, focusing on the integration of computational proteomics and AI in the context of cancer precision medicine. This is a unique opportunity to contribute to groundbreaking research aimed at enhancing personalized cancer treatments.
Doctoral (PhD) Student Position in Computational Proteomics and AI for Cancer Precision Medicine, Sweden
Designation
PhD Student in Computational Proteomics and AI for Cancer Precision Medicine
Table
| Category | Details |
|---|---|
| Research Area | Cancer Biology, Computational Proteomics, Bioinformatics |
| Location | Science for Life Laboratory, Karolinska Institutet, Stockholm, Sweden |
| Eligibility/Qualification | Master’s degree in Computer Science, Bioinformatics, Biostatistics, Mathematics, Systems Biology, or related fields; Strong programming skills in Python/R; Experience with machine learning and AI methods |
| Job Description | Analyze and integrate diverse proteomics data; reconstruct signaling networks; apply machine learning and AI for data interpretation; contribute to publications and seminars |
| How to Apply | Submit your application and supporting documents via the Varbi recruitment system. Include a personal letter, CV, degree projects, and certification documents as specified. |
| Last Date to Apply | 7th May 2026 |
Research Area
The position focuses on advancing proteome analysis and its application to individualized cancer treatments through experimental and computational methods in proteomics and proteogenomics, particularly concerning leukemia and solid tumors.
Location
The position is based at the Science for Life Laboratory (SciLifeLab) in Stockholm, Sweden, under the Department of Oncology-Pathology at Karolinska Institutet.
Eligibility/Qualifications
- A Master’s degree or equivalent in relevant fields (Computer Science, Bioinformatics, etc.)
- Strong programming skills in Python and/or R
- Experience with machine learning, deep learning, or AI methods
- Familiarity with omics data analysis is desirable
- Proficiency in English (written and spoken)
Job Description
The doctoral student will:
- Analyze diverse proteomics data across various cancer types.
- Reconstruct signaling networks at a single-cell resolution.
- Explore the application of advanced machine learning and AI methods, including large language models for functional annotation.
- Collaborate within a multi-disciplinary team and participate in scientific dissemination through seminars and publications.
How to Apply
Interested candidates should submit their application through the Varbi recruitment system, including:
- A personal letter
- Curriculum vitae
- Degree projects and previous publications (if applicable)
- Documentation supporting eligibility requirements
Last Date to Apply
Applications must be submitted no later than 7th May 2026.
This scholarship aims to foster innovative research that may enhance cancer treatment approaches, offering a valuable opportunity to work within a world-renowned institution.
