Postdoctoral fellow in Machine Learning with a focus on deep learning and applications in cardiology - Hiring in process/Finished, not possible to apply

The Department of Information Technology has a leading position in research and education. The Department currently has about 280 employees, including 120 teachers and 110 PhD students. More than 4000 students study one or more courses at the department each year. More info: http://www.it.uu.se/?lang=en

At the Division of Systems and Control, we develop methodology and concrete tools for learning, reasoning and acting based on measured data. One of the cornerstones in our research is a probabilistic model allowing us to systematically represent and cope with the uncertainty that is inherent in most data. An important goal is to develop flexible models that can capture complex dynamical phenomena and their environments allowing machines and humans to better understand the world around us. The data and the model are two of the cornerstones of our research. The third cornerstone is the learning algorithm, with the fundamental objective of automatically constructing models based on data. It remains a major challenge to develop efficient and accurate learning algorithms capable of handling high-dimensional models, data rich applications, complex model structures, and diverse data sources that arise in many of the data analysis problems that we are currently facing. The fourth and final cornerstone of our research is that of control. The main task here is to make use of all that has been learnt from the data and represented within the probabilistic model to automatically make decisions and influence the current situation in a suitable manner. Information about our research is available from this popular scientific description http://www.teknat.uu.se/news/nyhetsdetaljsida/id=9994&area=5,16,17,50&typ=artikel&lang=en

The Division of Systems and Control has a wide network of strong international collaborators all around the world, for example at the University of Cambridge, University of Oxford, University of British Columbia, University of Sydney, University of Newcastle and Aalto University.

Duties/Project description: Research in fundamental methods for machine learning and their application in cardiology. This postdoctoral position will intensify our work (both method development and applications) in deep learning and in particular its use when it comes to automatic interpretation of ECG recordings. The position might also include teaching in machine Learning.

Requirements: To qualify for an employment as a postdoctor you must have a PhD degree or a foreign degree equivalent to a PhD degree in a relevant field. The PhD degree must have been obtained no more than three years prior to the application deadline. 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 deep learning, as well as its use in automatic interpretation of ECG. Publications at leading conferences in machine learning is a requirement. A good knowledge of modeling of dynamic systems is also a prerequisite. Particular emphasis will be placed on relevant research in deep learning and its use for applications in cardiology, as well as experience according to the tasks described above.

The employment is for two years and can include teaching up to 20% depending on availability and interest. You are expected to be able to teach in Swedish or English. Excellent knowledge of oral and written English is a requirement.

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. A research statement describing your past and current research (max 1 page) and a proposal for future activities (max 1 page).

5. Contact information for two references.

6. A cover letter briefly describing your motivation for applying for this position and the earliest possible employment date (max 1 page).

Salary: Individual salary.

Starting date: As soon as possible.

Type of employment: Temporary position for 2 years according to central collective agreement.

Scope of employment: 100 %

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).

Please submit your application by 9th of October 2020, UFV-PA 2020/3222.

Are you considering moving to Sweden to work at Uppsala University? If so, you will find a lot of information about working and living in Sweden at www.uu.se/joinus. You are also welcome to contact International Faculty and Staff Services at ifss@uadm.uu.se.