Postdoctoral fellow in Machine Learning - Hiring in process/Finished, not possible to apply

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. Active researchers in Artificial Intelligence include Thomas Schön and David Sumpter (machine learning); Ida-Maria Sintorn and Caroline Wählby (AI and image analysis); Ginevra Castellano and Katie Winkle (social robotics); and Matteo Magnani (data science and networks).
Uppsala University’s has a long tradition of successful research – among its alumni are 16 Nobel Prize laureates, including, most recently, Svante Pääbo. The University is unique when it comes to combining IT with wider research, from life sciences to the humanities, and this collaboration is currently facilitated by AI4Research and the Centre for Interdisciplinary Mathematics.

The IT 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 and teaching staff actively develop new approaches to education.

Duties/Project description
Research on fundamental models and methods in machine learning and their applications within medicine. The position is part of an ERC Advanced Grant focused on developing decision support for the emergency room. The work will be done in close collaboration with our medical partner Professor Johan Sundström who leads the Anders Wiklöf Institute for Heart Research. We already share offices and our groups have collaborated for quite some time.

The postdoctoral position will intensify our work on developing and analyzing methods in machine learning and their application within medicine. We will continue our work on extracting knowledge from large-scale ECG data sets, and we will utilize large databases with electronic health records and patient-reported data and three-dimensional symptom drawings. The aim is to be able to investigate the use of these models for decision support and the position can also include work on decision algorithms. Technical keywords for the position include: probabilistic models, decision making algorithms, deep learning, Bayesian inference and precision medicine. The position might also include teaching.

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Duties/Project description
Research on fundamental models and methods in machine learning and their applications within medicine. The position is part of an ERC Advanced Grant focused on developing decision support for the emergency room. The work will be done in close collaboration with our medical partner Professor Johan Sundström who leads the Anders Wiklöf Institute for Heart Research. We already share offices and our groups have collaborated for quite some time.

The postdoctoral position will intensify our work on developing and analyzing methods in machine learning and their application within medicine. We will continue our work on extracting knowledge from large-scale ECG data sets, and we will utilize large databases with electronic health records and patient-reported data and three-dimensional symptom drawings. The aim is to be able to investigate the use of these models for decision support and the position can also include work on decision algorithms. Technical keywords for the position include: probabilistic models, decision making algorithms, deep learning, Bayesian inference and precision medicine. The position can include teaching up to 20% depending on availability and interest. 

Requirements
PhD degree within machine learning, signal processing, computer vision, computational statistics or another nearby and relevant field or a foreign degree equivalent to a PhD degree within machine learning, signal processing, computer vision, computational statistics or another nearby and relevant field. 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 applicant must have a strong background in method development and the use of machine learning. The ability to make use of deep learning is required. Publications at leading conferences in machine learning is a strong plus. You are expected to be able to teach in Swedish or English. Excellent knowledge of oral and written English is a requirement.

Additional qualifications
Experience of interdisciplinary research is good. As a person, you are creative, thorough and have 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 professional approach and to analyze and work with complex problems. Great emphasis will be placed on personal characteristics and personal suitability.

Application
The application must contain:

1. A curriculum vitae (CV),
2. A copy of relevant grade documents (translated into Swedish or English),
3. A list of publications
4. Up to five selected publications in electronic format
5. A research statement describing your past and current research (max 1 page) and a proposal for future activities (max 1 page).
6. Contact information for two references.
7. A cover letter briefly describing your motivation for applying for this position and the earliest possible employment 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 soon as possible or as agreed. Placement: Uppsala.

For further information about the position, please see http://www.it.uu.se/ (the department) or contact: Prof. Thomas Schön (thomas.schon@it.uu.se) or Associate Professor Dave Zachariah (dave.zachariah@it.uu.se).

Please submit your application by 1 March 2023, UFV-PA 2023/233.

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