Researcher position in Computerized Image Processing - Hiring in process/Finished, not possible to apply

The position is hosted at the Department of Information Technology at Uppsala University, within the Methods for Image Data Analysis group of the Division of Visual Information and Interaction.

The Department of Information Technology has approximately 300 employees and conducts research and education in a wide spectrum of areas within Computer Science and Information Technology. The research is organized in five Divisions, where the Division of Visual Information and Interaction provides a combination of expertise in Computerized Image Analysis and Human-Computer Interaction. More information about the department and its activities can be found at https://www.it.uu.se.

The research at the Division of Visual Information and Interaction is conducted in several research groups. The Methods for Image Data Analysis (MIDA) group focuses on research and development of general methods for image data analysis, aiming to devise generally applicable methods that work well, independent of the particular application and types of images used. Striving for practically useful methods, the research is typically driven by applications, often from the fields of biomedicine and medicine. The research is multidisciplinary and often connects with several other research groups and disciplines. More information about the research of the MIDA group can be found at https://www.it.uu.se/research/visual_information_and_interaction/research/mida.

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Research project
The position is funded through two closely related VINNOVA projects, “AI-Driven Large-scale Screening for Oral and Oropharyngeal Cancer” and “Multimodal imaging and information fusion for confident image-based cancer diagnostics”. Through exploring and developing novel deep learning based techniques for multimodal information fusion we aim to improve understanding of oral and oropharyngeal cancer, its causes and progression, and enable reliable early detection and confident differentiated diagnosis, thereby providing a solid basis for treatment planning. Explainability is seen as a key component of successful deployment of AI in healthcare and is therefore an essential part of the project. In collaboration between Uppsala University, Center for Clinical Research Dalarna, and Folktandvården Stockholms Län AB, we will, through AI-based data fusion, combine information from several imaging techniques to capture complementary information about a specimen. With the goal of large-scale implementation and usage in everyday healthcare in Sweden and India we aim to explore privileged information scenarios where multimodal information on limited data can be used to elevate performance of larger monomodal data.

Duties
The position envisions 100% research time, focused on the tasks described in the project plans of the two funding projects, “AI-Driven Large-scale Screening for Oral and Oropharyngeal Cancer” and “Multimodal imaging and information fusion for confident image-based cancer diagnostics”, primarily within the areas of computerized image processing and machine learning.

You are expected to take initiative and responsibility in advancing the projects and also to contribute with proposals for the direction of the research. There exists a level of freedom to develop your ideas within the overall framework of the project. You are assumed to take an active role in the MIDA research environment and contribute to the development of the research milieu.

The work includes method development, implementation, data management, evaluation and analysis, manuscript preparation, student supervision and own career development. Assisting PhD students in the research group will be a part of the duties, as well as taking part in writing applications for external funding for continued research. The position may also entail some research-administrative tasks.

The work will be conducted in collaboration with researchers at the Center for Clinical Research Dalarna, and Folktandvården Stockholms Län AB. Frequent and open communication with the involved parties is expected.

Requirements
The candidate should have a PhD degree in Computerized Image Analysis/Processing or a closely related field. 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 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.
Fluency in spoken and written English is required.

Additional qualifications
Personal qualities such as dedication, motivation, initiative and independence, as well as ability to work in a team, are valued.
It is meriting if the candidate has experience of university level teaching and supervision. Experience of programming in JavaScript, C++, Matlab, Java, software version control with Git, typesetting with LaTeX, use and administration of Linux computers, Bash scripting, counts as meriting. Experience of multimodal image data analysis is a strong advantage.

The application should consist of:

1. A Curriculum Vitae (CV);
2. A copy of degree/diploma, 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;
7. Contact information for two references;
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, 12 months. Scope of employment 100 %. Starting date as soon as possible or as agreed. Placement: Uppsala.

For further information about the position, please contact: Professor Joakim Lindblad (phone: +46  733 168549, email: joakim.lindblad@it.uu.se) or Professor Nataša Sladoje (phone: +46 721 828722, email: natasa.sladoje@it.uu.se).

Please submit your application by 17 March 2022, UFV-PA 2022/680.

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