Summary
KTH Royal Institute of Technology is offering a unique scholarship opportunity for a doctoral student in deep learning focused on mass spectrometry data. This position is part of the Data-Driven Life Science (DDLS) Research School, aiming to enhance the interpretation and matching of mass spectrometry data through advanced computational tools.
Designation
PhD Student in Deep Learning for Mass Spectrometry Data
| Details | Information |
|---|---|
| Research Area | Biotechnology, mass spectrometry, deep learning |
| Location | Stockholm, Sweden |
| Eligibility/Qualification | – Master’s degree or equivalent – Knowledge of English (B/6) |
| Job Description | – Develop probabilistic deep learning models – Work with computational tools on proteomics data – Collaborate with researchers and students |
| How to Apply | Apply through KTH’s recruitment system, providing required documents and a motivation letter |
| Last Date to Apply | 13 May 2026 |
Research Area
The scholarship focuses on developing computational methods in the field of biotechnology with a specific emphasis on proteomics and mass spectrometry.
Eligibility/Qualification
- Passed a second-cycle degree (e.g., master’s degree) or equivalent.
- Completed course requirements of at least 240 higher education credits, including 60 at the second cycle.
- Proficiency in English equivalent to English B/6.
- Preferred background includes experience in machine learning, deep learning (especially transformer architectures), and programming in Python (preferably with PyTorch).
Job Description
The selected applicant will:
- Engage in research to improve the interpretation and matching of mass spectrometry data.
- Collaborate with supervisors, other doctoral students, and postdocs.
- Utilize and develop new models for proteomics data interpretation.
How to Apply
Interested candidates must ensure their applications are complete and submitted through KTH’s recruitment system. The application should include:
- Copies of diplomas and grades.
- A CV detailing relevant experience.
- A motivation letter (max 2 pages) explaining the applicant’s research interests.
- Any representative publications or technical reports.
Last Date to Apply
Applications must be submitted by 13 May 2026.
For full details, you can visit KTH’s website.
