Research Engineer in Deep Learning for Breast Cancer Recognition
Royal Institute of Technology School of Electrical Engineering and Computer Science
Sweden

Research Engineer in Deep Learning for Breast Cancer Recognition

School of Electrical Engineering and Computer Science at 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.

Job description

The candidate will be responsible for developing software and tools to support our ongoing research project and clinical trial on deep learning for mammographic images. The candidate will be responsible for training and deploying neural networks, curating datasets, and other technical tasks associated with the project. The candidate will need a strong technical background in machine learning and mathematics, but must also be capable of communicating with doctors on a regular basis. The candidate will likely be involved in the writing of scientific articles.

What we offer

  • 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 get settled in Sweden and at KTH.

Read more about what it is like to work at KTH

Qualifications

Requirements

  • A graduate degree or an advanced level (higher education) in the research subject or equivalent competence. 
  • Additional requirements for the position
  • A strong mathematics background
  • Proficient in Python
  • Experienced with PyTorch and TensorFlow
  • Familiar with a Linux environment
  • Have strong technical writing

Preferred qualifications

Knowledge and skills that are meritorious for the position:

  • Subject-related skills
  • Professional skills
  • Awareness of diversity and equal opportunity issues, with specific focus on gender equality
  • Collaborative abilities
  • Independence

Great emphasis will be placed on personal competency.

Trade union representatives

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

Application

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.

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.

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

About the employment

The employment is valid for a limited time according to the agreement - for up to 12 months, with access according to agreement.

Other information

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. 

Type of employment Temporary position longer than 6 months
Contract type Full time
First day of employment According to agreement
Salary Monthly salary
Number of positions 1
Working hours 100%
City Stockholm
County Stockholms län
Country Sweden
Reference number J-2021-1655
Contact
Kevin Smith, Associate professor, ksmith@kth.se
Natasha Kapama, HR, kapama@kth.se
Published 06.Jul.2021
Last application date 06.Aug.2021 11:59 PM CEST


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