Summary
KTH Royal Institute of Technology is hiring a Postdoctoral Researcher to develop AI/Machine Learning workflows for the quantitative analysis of lipid nanoparticles (LNPs) using Cryo-EM. The position is based at the Barriga Lab within the Division of NanoBiotechnology (Department of Protein Science) at SciLifeLab, Solna/Stockholm, in close collaboration with the Cryo-EM facility at SciLifeLab.
Postdoc in Developing AI/ML Workflow for Quantitative Analysis of Lipid Nanoparticles
Key Information Overview
| Attribute | Details |
| Designation | Postdoctoral Fellow / Postdoc |
| Institution | KTH Royal Institute of Technology |
| Department / Division | School of Engineering Sciences in Chemistry, Biotechnology and Health / Division of NanoBiotechnology (Department of Protein Science) |
| Research Group | Barriga Lab (in collaboration with SciLifeLab Cryo-EM Facility) |
| Location | Stockholm / Solna, Sweden |
| Employment Type | Full-time, Temporary (up to 2 years) |
| Reference Number | PA-2026-2753 |
| Contact Person | Hanna Barriga (barriga@kth.se) |
| Start Date | September 2026 or by agreement |
| Application Deadline | August 28, 2026 (Midnight CET/CEST) |
Designation
Postdoctoral Fellow (Postdoc)
Research Area
- Artificial Intelligence & Machine Learning (AI/ML): Automated image analysis pipelines and quantitative workflow development.
- Structural Biology & Biophysics: Cryo-Electron Microscopy (Cryo-EM), Small-Angle Scattering (SAS).
- Nanomedicine & Drug Delivery: Lipid nanoparticles (LNPs) and structure-function relationships in lipid systems.
Location
- City/Region: Solna / Stockholm, Sweden
- Facility: Science for Life Laboratory (SciLifeLab) / KTH Royal Institute of Technology
Job Description
Quantitative analysis of lipid nanoparticles (LNPs) using Cryo-EM is challenging due to heterogeneous samples, lack of training data, and sample variability. This project aims to design and implement AI/ML workflows for improved quantitative analysis of LNPs.
Key Responsibilities:
- Optimizing data collection parameters for automated analysis pipelines.
- Developing, optimizing, and implementing AI/ML workflows.
- Validating analysis results using physicochemical approaches.
- Collaborating closely with experimental LNP PhD/Postdoc projects in the Barriga Lab and with the Cryo-EM facility at SciLifeLab (M. Carroni).
- Assisting with supervision/co-supervision of Master’s/PhD students, teaching, and contributing to grant applications or collaborative initiatives.
Eligibility & Qualifications
Requirements:
- A doctoral degree (Ph.D.) or equivalent foreign degree (must be completed by the time the employment decision is made).
- Demonstrated expertise in large-scale data handling.
- Hands-on experience working with Cryo-EM.
- Experience supervising or co-supervising Master’s or PhD students.
- Proven track record of multidisciplinary collaboration and teamwork.
- Demonstrated ability to conduct independent research.
Preferred Qualifications:
- A Ph.D. degree obtained within the last three years prior to the application deadline.
- Experience working with lipid nanoparticles (LNPs).
- Experience with small-angle scattering (SAS) techniques.
- Strong written and verbal communication skills in English.
- Awareness of diversity and equal opportunity issues (with a specific focus on gender equality).
How to Apply
Applications must be submitted electronically through the KTH Recruitment Portal.
Required Documents:
- Curriculum Vitae (CV): Detail your relevant professional experience, research background, and publications.
- Diplomas and Transcripts: Copies of previous university degrees/transcripts (with certified English or Swedish translations if the original documents are in another language).
- Cover Letter (Max 2 pages): Outlining your motivation for the research, academic interests, alignment with your background and career goals, and key competencies relevant to this role.
Last Date to Apply
August 28, 2026 (23:59 / Midnight CET/CEST)
