Postdoc in medical image processing focusing on heart and lungs

We are recruiting a postdoctoral fellow, who will conduct research in the field of medical image processing targeting coronary artery disease and obstructive pulmonary disease.

Computed Tomography (CT) produces high-resolution images av the heart and coronary vessels as well as the lungs. In order to improve clinical diagnosis, our group is developing new methods for quantitative image analysis methods based on modern machine learning techniques such as deep learning with Convolutional neural networks (CNN), Graph convolutional networks (GCNN) and Variational autoencoders (VAE), combined with Computational fluid dynamics (CFD). Image data for this purpose are available through the national population-based project Swedish CArdioPulmonary bioImage Study (SCAPIS).

As a postdoc you will independently develop such methods, resulting in scientific publications and presentations at international conferences.

• 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
• Stimulating cross-disciplinary collaboration including technical as well as medical expertise
• 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

Requirements

• A doctoral degree or an equivalent foreign degree. This eligibility requirement must be met no later than the time the employment decision is made.
• The candidate must have a strong background in at least one of the following areas: medical image processing, medical imaging, machine learning or a similar subject.
• Proficiency in English orally and in writing is required to present and publish research results.

Preferred qualifications

• A doctoral degree or an equivalent foreign degree, obtained within the last three years prior to the application deadline
• Strong research qualifications
• Good programming skills, in particular with libraries used for deep learning
• Good collaborative abilities as we work in a team
• Experience of working in a cross-disciplinary setting
• Have the ability to work independently
• Good teaching abilities
• Awareness of diversity and equal opportunity issues, with specific focus on gender equality

Great emphasis will be placed on personal competency.

You will find contact information to trade union representatives at KTH's webbpage .

Log into KTH's recruitment system in order to apply to this position. You are the main responsible to ensure that your application is complete according to the ad.

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).

The application must include

• CV including relevant professional experience and knowledge.
• 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.
• No more than three examples of earlier scientific publications where you have been the main author.
• Brief account of why you want to conduct research, your academic interests and how they relate to your previous studies and future goals. Max two pages.

The position offered is for, at the most, two 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.

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 please read here.

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.