Uppsala University, Department of Information Technology

Uppsala University is a comprehensive research-intensive university with a strong international standing. Our ultimate goal is to conduct education and research of the highest quality and relevance to make a long-term difference in society. Our most important assets are all the individuals whose curiosity and dedication make Uppsala University one of Sweden’s most exciting workplaces. Uppsala University has over 54,000 students, more than 7,500 employees and a turnover of around SEK 8 billion.

Uppsala University has a long tradition of groundbreaking research – among its alumni are 16 Nobel Prize laureates, including, most recently, Svante Pääbo. The University is unique in combining IT and Artificial Intelligence with other research, from life sciences to humanities. Such interdisciplinary collaboration is facilitated by the Centre for Image Analysis, AI4Research, the Centre for Interdisciplinary Mathematics, and several others.

The Department of Information Technology has a leading position in research and education. The Department currently has about 300 employees, including 120 teachers and 110 PhD students. More than 4000 students study one or more courses at the department each year. You can find more information about us at the web page of the department of Information Technology

The Department is situated in the newly built Ångström House 10, which offers a modern and inspiring work environment and research facilities. Researchers work on a broad spectrum of topics, from designing processors, through social robotics and cybersecurity, to developing methods in image analysis and machine learning, while also supporting cancer research with computational tools. 

Research at the Department is conducted within several research groups. The MIDA Methods for Image Data Analysis – group focuses on development of methods for image data analysis, aiming to devise generally applicable approaches and tools that work well, independent of the particular application and types of images used. Striving for practically useful methods with a real and prominent impact, the research is often driven by emerging needs from the fields of biomedicine and medicine. The research is multidisciplinary and often connects with several other research groups and disciplines. MIDA is closely linked to the Centre for Image Analysis, and actively participates in European and global networks of image analysts in life sciences.

Read more about our benefits and what it is like to work at Uppsala University

Research project: Interpretable AI-based multispectral 3D-analysis of cell interrelations in the cancer microenvironment

Immunotherapy has become a life-saving option for advanced cancer patients. However, only a minority of patients develop a durable response. Despite great efforts to explain the variable responses to immunotherapy and to optimize patient selection, current diagnostic tools cannot sufficiently guide clinical practice. This project will combine state-of-the-art multiplexed microscopy with the latest techniques of image processing and deep learning to radically advance the understanding of how cell interrelations in the tumor microenvironment affect the disease progression and treatment efficacy, ultimately leading to improved treatments and saved lives.

Starting from a large collection of acquired multispectral histology images, the project aims to develop advanced interpretable AI-driven approaches for image data analysis, for characterization of the structural 3D organization and interrelations of different cell types, enabling reliable and explainable prediction of patient disease progression.

This project heavily relies on interdisciplinary competences and will be conducted in close collaboration with the researchers at the Department of Immunology, Genetics and Pathology (IGP) at Uppsala University. IGP has a broad research profile with strong research groups focused on cancer, autoimmune and genetic diseases, and promotes translational research, with close interactions between medical research and health care. (Notably, Nobel Laureate Svante Pääbo was a guest researcher at IGP 2003–2015.)

The position is funded through research projects conducted by the MIDA group and financed by Cancerfonden (Swedish Cancer Society)  and Swedish Research Council (Vetenskapsrådet).

The successful candidate will join the MIDA group and take initiative and responsibility for development and evaluation of advanced AI-based methods for analysis of multidimensional images of cancer tissue, towards optimized immunotherapy for cancer patients.

The duties include method development, implementation, data management, evaluation and analysis, manuscript preparation, master student supervision and own career development. Assisting PhD students in the research group on the related research tasks will be a part of the duties. The position may also entail some research-administrative tasks. Teaching in related subjects (max 20%) can also be included depending on availability and interest.

The successful candidate is expected to contribute with their own ideas for the research directions within the overall framework of the project. The candidate is expected to take an active role in the MIDA research environment and contribute to the development of the research milieu.

PhD degree in a field closely related to the position (e.g., computerized image analysis/processing, data science, computer science or a foreign degree equivalent to a PhD degree in a field closely related to the position (e.g., computerized image analysis/processing, data science, computer science. The degree needs to be obtained by the time of the decision of employment. Those who have obtained a PhD degree three years prior to the application deadline are primarily considered for the employment. The starting point of the three-year frame period is the application deadline. Due to special circumstances, the degree may have been obtained earlier. The three-year period can be extended due to circumstances such as sick leave, parental leave, duties in labour unions, etc.

The candidate must have documented experience in image analysis, machine and deep learning, including completed courses at the master and doctoral level of education, as well as first hand experience in method development, implementation, evaluation, and publication (first author) of scientific articles in internationally recognized journals and presentations at international conferences. Programming in Python, and experience of working with deep learning in the PyTorch environment is a requirement.

As a person, a successful candidate is motivated, creative, dedicated, responsible, and has a structured approach. When selecting among the applicants we will assess their ability to independently drive their work forward, to collaborate with others, to have a diligent and professional approach and to analyze and address complex problems. An emphasis will be placed on personal characteristics and personal suitability.

Fluency in spoken and written English is required.

Additional qualifications
Meriting are: 

  • Experience with graph-based methods, network analysis tools, and graph convolutional/neural networks;
  • Experience with explainable AI (XAI);
  • Experience of university level teaching and supervision;
  • Experience of programming in Matlab, JavaScript, C++, Java, software version control with Git, typesetting with LaTeX, use and administration of Linux computers, Bash scripting;
  • Interest in biomedical research and experience in application of image analysis in medicine.

The application should consist of:

  1. A Curriculum Vitae (CV);
  2. A copy of degree/diploma (translated into Swedish or English), with the list of relevant completed courses;
  3. List of publications;
  4. Up to five selected publications in electronic form, with stated own contributions;
  5. PhD thesis in electronic form;
  6. Description of your current and previous research (max 1 page) and suggestions for future research (max 1 page) along the project goals relevant for this position. The statement should explain how your profile fits the position;
  7. Contact information for two references (name, e-mail, and phone number);
  8. A personal letter in which you briefly justify why you are applying for this position and state the earliest possible starting date (max. 1 page).

About the employment
The employment is a temporary position of 2 years according to central collective agreement. Scope of employment 100 %. Starting date: As agreed. Placement: Uppsala.

For further information about the position, please contact: Prof. Nataša Sladoje (phone: +46 721 828 722; email: natasa.sladoje@it.uu.se ); Prof. Joakim Lindblad (phone: +46 733 168549; email: joakim.lindblad@it.uu.se ).

Please submit your application by the 6th of April 2023, UFV-PA 2023/680.

Are you considering moving to Sweden to work at Uppsala University? Find out more about what it´s like to work and live in Sweden.  

Type of employment Temporary position
Contract type Full time
First day of employment As agreed
Salary Fixed salary
Number of positions 1
Full-time equivalent 100%
City Uppsala
County Uppsala län
Country Sweden
Reference number UFV-PA 2023/680
Union representative
  • Seko Universitetsklubben, seko@uadm.uu.se
  • ST/TCO, tco@fackorg.uu.se
  • Saco-rådet, saco@uadm.uu.se
Published 01.Mar.2023
Last application date 06.Apr.2023 11:59 PM CEST

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