Job description

Are you looking for a postdoc combining academic research in machine learning with close collaboration with the industry? Do you want to join our research group at KTH developing fundamental machine learning times series algorithms and the team at Getinge producing the next generation ventilators for the intensive care? Are you passionate about physical simulation and proficient in parameter estimation? If so, we believe you will find our project developing a digital twin of the respiratory system a perfect match.

This project is co-funded by Vinnova, within the program Advanced Digitalization, and Getinge. Getinge is a world leading MedTech provider with 12.000 employees worldwide. The company has a long tradition of creating innovations that save lives. Their Critical Care Product Area is based in Stockholm, Sweden, and you will interact with its Innovation team regularly during this project. The close collaboration with this multi-disciplinary team of experts is a valuable opportunity for you to create a bridge between academia and industry, in an open and collaborative way. This is also a unique chance that will open multiple future career paths for you.

What we offer

• We offer a dynamic environment where academic research meets industrial R&D, where fundamental aspects of machine learning are combined with physical modelling and applied to intensive-care ventilators to save human lives.
• 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
• Help to relocate and be settled in Sweden and at KTH

Read more about what it is like to work at KTH

Qualifications

Requirements

• A doctoral degree or an equivalent foreign degree in machine learning, engineering physics, computer science or electrical engineering. This eligibility requirement must be met no later than the time the employment decision is made.
• Research expertise including machine learning, modeling and simulation as well as parameter estimation.
• As a person, you possess both collaborative abilities as well as the capacity to work independently. 

Preferred qualifications

• A doctoral degree or an equivalent foreign degree, obtained within the last three years prior to the application deadline.
• PhD or master degree experience in time series machine learning, dynamical systems theory and simulation including ODE-models.
• Experience and knowledge of biomedical applications.
• Experience and teaching abilities in machine learning.
• Awareness of diversity and equal opportunity issues, with specific focus on gender equality

Great emphasis will be placed on personal skills.

Trade union representatives

Contact information to trade union representatives.

To apply for the position

Log into KTH's recruitment system to apply for this position. You are responsible for ensuring that your application is complete according to the instructions in the ad. The application must include:

• A personal letter. Brief account of why you want to conduct research, your academic interests and how they relate to your previous studies and future goals. Maximally two pages long.
• CV including relevant professional experience and knowledge.
• Publication list
• Copy of diplomas and grades from your previous university studies. Translations into English or Swedish if the original documents have not been issued in any of these languages.

Your complete application must be received at KTH no later than the last day of application, midnight CET/CEST (Central European Time/Central European Summer Time).

About the employment

The position offered is for, at the most, three years.

A position as a postdoctoral fellow is a time-limited qualified appointment focusing mainly on research, intended as a first career step after a dissertation.

Others

Striving towards gender equality, diversity and equal conditions is both a question of quality for KTH and a given part of our values.

For information about processing of personal data in the recruitment process.

According to The Protective Security Act (2018-585), the candidate must undergo and pass security vetting if the position is placed in a security class. Information regarding whether the position is subject to such a classification will be provided during the recruitment process.

We firmly decline all contact with staffing and recruitment agencies and job ad salespersons.

Disclaimer: In case of discrepancy between the Swedish original and the English translation of the job announcement, the Swedish version takes precedence.

About KTH

KTH Royal Institute of Technology in Stockholm has grown to become one of Europe’s leading technical and engineering universities, as well as a key centre of intellectual talent and innovation. We are Sweden’s largest technical research and learning institution and home to students, researchers and faculty from around the world. Our research and education covers a wide area including natural sciences and all branches of engineering, as well as architecture, industrial management, urban planning, history and philosophy. Read more here

Type of employment: Temporary position
Contract type: Full time
First day of employment: According to agreement
Salary: Monthly salary
Number of positions: 1
Full-time equivalent: 100%
City: Stockholm
County: Stockholms län
Country: Sweden
Reference number: J-2024-1793
Contact:

1. Professor Erik Fransén, erikf@kth.se
2. Patrick Sjöstedt (HR-frågor), pss@kth.se

Published: 2024-06-28
Last application date: 2024-09-06