UU
Umeå UniversityPostdoc Fellowship in AI-Driven Medical Imaging at Umeå University
Fully FundedUmeå, Swedenpostdoctoral· Scholarship stipend for 2 years (amount not specified).
Project Overview
2-year postdoctoral fellowship in AI-driven medical imaging at Umeå University. Focus on reducing operator dependence in ultrasound. Starts 1 Sept 2026. Apply by 30 Sept 2026.
Project Description
The Department of Diagnostics and Intervention at Umeå University invites applications for a two-year postdoctoral fellowship within the project AI-Driven Medical Imaging. The position is expected to start on 1 September 2026 or as agreed. The fellowship is funded by The Kempe Foundations.
The aim is to develop and evaluate AI-based methods that reduce operator dependence in ultrasound imaging, with focus on clinically relevant applications. The research is conducted within a well-established research group led by Christer Grönlund, specialising in methodological development in medical ultrasound imaging.
Main Application Areas
1. Atherosclerosis diagnostics: Early identification of pathophysiological phenotypes, decentralised examinations, and reduced operator dependence.
2. Diagnostics of skeletal muscle diseases: Non-invasive ultrasound-based methods as alternatives to needle-based diagnostic techniques. Advanced analysis of motor units, translating methods from research systems to clinical ultrasound scanners.
Methods to Develop
- Anomaly detection
- Domain adaptation
The Department of Diagnostics and Intervention at Umeå University invites applications for a two-year postdoctoral fellowship within the project AI-Driven Medical Imaging. The position is expected to start on 1 September 2026 or as agreed. The fellowship is funded by The Kempe Foundations.
The aim is to develop and evaluate AI-based methods that reduce operator dependence in ultrasound imaging, with focus on clinically relevant applications. The research is conducted within a well-established research group led by Christer Grönlund, specialising in methodological development in medical ultrasound imaging.
Main Application Areas
1. Atherosclerosis diagnostics: Early identification of pathophysiological phenotypes, decentralised examinations, and reduced operator dependence.
2. Diagnostics of skeletal muscle diseases: Non-invasive ultrasound-based methods as alternatives to needle-based diagnostic techniques. Advanced analysis of motor units, translating methods from research systems to clinical ultrasound scanners.
Methods to Develop
- Anomaly detection
- Domain adaptation
Closing soon · 19 daysApply on official site ↗