Researcher position in image analysis and deep learning - Hiring in process/Finished, not possible to apply

Are you interested in working with the development of new image processing and deep learning methods for the application of automated imaging and quality assessment of grain, with the support of competent and friendly colleagues in an international environment? Are you looking for an employer that invests in sustainable employeeship and offers safe, favourable working conditions? We welcome you to apply for a researcher position in image analysis and deep learning at Uppsala University.

The Department of Information Technology holds a leading position in both research and education at all levels. We are currently Uppsala University's third largest department, have around 350 employees, including 120 teachers and 120 PhD students. Approximately 5,000 undergraduate students take one or more courses at the department each year. You can find more information about us on the department of Information Technology website.

The Department of Information Technology is situated in the newly built Ångström House 10, which contains a visualization studio, a social robot lab, a maker space and 3D printing workshop. Researchers work in all areas of IT, from designing processers, through HCI and cybersecurity, to cancer research tools and methods for numerical analysis and machine learning. The research work takes place in a multidisciplinary division in a group with  focus on image processing and machine learning with applications in medical imaging, microscopy, and text recognition The division is based at the Department of Information Technology at Uppsala University and has a strong national and international network.

Cgrain
This position is for research within a research project with Cgrain, a Swedish Uppsala based agri-tech company partly owned by Lantmännen. Cgrain develops, produces and sells instruments for automated vision based grain quality assessment. A sample of grain is poured into the instrument and each kernel is imaged from multiple directions whereafter the image is analyzed to assess whether the kernel is broken, has mold, color defects, diseases, insect infestation etc. As an early technology adopter, Cgrain has for the last few years utilized deep learning (AI) methods to train deep neural networks model to perform the image-based grain classification.

Duties
The research project is on developing and evaluating methods for classification and quantification of images of grain kernels. The overall project aim is to improve image based grain quality analysis performance, and to increase the understanding of when, why and how a trained AI model can be reliably used. In addition, it aims at exploring expert assisted training and validation strategies for reliable and sustainable AI deployment. For example, to develop interactive visualization tools to identify errors and problematic classes and strategies for exploring how knowledge of such weaknesses can be incorporated in the AI models for continuous improvement. The duties for this position mainly consist of performing research striving towards the project goals together with the project leader from UU and project members at Cgrain. To prepare and present results in internal meetings as well as in scientific and popular science publications and conferences are also duties included in the position. In addition to research, the position contains up to 20% teaching.

Requirements
To qualify for an employment as a researcher you must have a PhD degree or a foreign degree equivalent to a PhD degree in Image Processing or Computer Vision, or another nearby and relevant field.

Additional qualifications
Experience in research and method development in image processing and deep learning is an advantage. Pedagogic training and teaching experience as well as collaboration skills are also meriting.

About the employment
The employment is a temporary position for 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: Ida-Maria Sintorn, 018-4713471, ida.sintorn@it.uu.se

Please submit your application by 15 January 2024, UFV-PA 2023/4788.

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