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Postdoctoral Researcher in Physics-Based Machine Learning
2 months ago
We are seeking a highly skilled postdoctoral researcher to join our team at KTH Royal Institute of Technology in Stockholm, Sweden. The successful candidate will work on a project developing a digital twin of the respiratory system, combining academic research in machine learning with close collaboration with the industry.
Key Responsibilities- Conduct research in machine learning, focusing on physics-based modeling and simulation of respiratory systems.
- Collaborate with the Innovation team at Getinge, a world-leading MedTech provider, to apply machine learning algorithms to intensive-care ventilators.
- Develop and implement machine learning models for parameter estimation and prediction of respiratory system behavior.
- Work closely with the research group at KTH to integrate machine learning with physical simulation and parameter estimation.
- PhD in machine learning, engineering physics, computer science, or electrical engineering.
- Research expertise in machine learning, modeling, and simulation, as well as parameter estimation.
- Excellent programming skills in languages such as Python, C++, or MATLAB.
- Strong communication and collaboration skills, with the ability to work independently and as part of a team.
- Experience in time series machine learning, dynamical systems theory, and simulation, including ODE models.
- Knowledge of biomedical applications and experience in teaching machine learning.
- Awareness of diversity and equal opportunity issues, with a focus on gender equality.
- A dynamic environment where academic research meets industrial R&D.
- A position at a leading technical university that generates knowledge and skills for a sustainable future.
- Engaged and ambitious colleagues, along with a creative, international, and dynamic working environment.
- Work in Stockholm, in close proximity to nature.
To apply for this position, please log into KTH's recruitment system and submit your application, including a personal letter, CV, publication list, and copies of diplomas and grades from previous university studies. The application deadline is midnight CET/CEST on the last day of application.
