Postdoc in machine learning for biomedical image analysis

KTH

Application deadline

October 23, 2023



Postdoc in machine learning for biomedical image analysis

Job description

We are currently looking for two postdocs, one with the focus on optical microscopy of live cells and one on machine learning, for a joint project between the Department of Applied Physics and the Division of Robotics, Perception and Learning at KTH.

The goal of this project is to explore advanced microscopy methods in combination with recent methods in deep learning to identify cells with particular functional properties, such as immune cells and their abilities to kill tumor cells. We will exploit methods that have shown promising results in other application areas, but further develop and refine them for biomedical imaging. To automatically identify and harvest cells with certain functional properties has far-reaching potential benefits.

The project is financed by the two large research programs in Sweden, the Wallenberg AI, Autonomous Systems and Software Program (WASP), and the SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS), with the joint goal to solve ground-breaking research questions across disciplines.

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 be settled in Sweden and at KTH
  • Plenty of collaboration opportunities in a dynamic research group
  • A research environment with strong base within microscopy for bio applications and easy access to advanced optical microscopes
  • Easy access to GPU clusters and supercomputers

Read more about what it is like to work at KTH

Qualifications

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.
  • Independence, demonstrated in research by e.g., first-author publications in high-quality conferences or journals
  • Good level of spoken and written English to facilitate collaborations 

Preferred qualifications

  • A doctoral degree or an equivalent foreign degree, obtained within the last three years prior to the application deadline
  • A strong background in microscopy and fluorescence labeling of cells
  • A strong background in cell culture, isolation of cells from blood or tissue
  • Experience of image analysis, machine learning or related fields.
  • Practical experience of programming
  • An interest in multi-disciplinary research
  • Teaching abilities
  • Awareness of diversity and equal opportunity issues, with specific focus on gender equality

Personal skills

  • You are interested in collaborating with others, with doctoral students in particular
  • You can work independently when necessary
  • You enjoy working in a socially diverse group with people of different genders, ethnicity, beliefs and backgrounds.

Great emphasis will be placed on personal skills.

Trade union representatives

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

To apply for the position

Log into KTH’s recruitment system in order to apply for 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.
  • 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 long.

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).

Last updated: 2023-10-05

Content Responsible: victor kuismin(victor.kuismin@scilifelab.uu.se)