Doctoral Student position in Deep Learning for Mammography Image Analysis

Research Unit of Medical Imaging, Physics and Technology, Faculty of Medicine, University of Oulu

Description of the position
Recently, Deep Learning (DL) has become widely popular and shows an enormous potential in revolutionizing the healthcare system in different fields. In this project, we are going to develop a new generation of DL-based diagnostic systems for breast cancer detection using mammography with a validation in a real clinical setting at Oulu University Hospital. We are looking for a talented individual with a strong mathematical and engineering background. The successful candidate will be working in a highly multidisciplinary environment with close contact to the experts in several fields: radiologists, medical physicists as well as machine learning and computer vision experts.

Research environment
The research will be conducted at Research Unit of Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Finland (, MIPT is an international environment of best national and international experts in medical research: neuroscience, osteoarthritis imaging and diagnosis, and health technologies. Our unit is highly interdisciplinary consisting of specialists from different fields. After acceptance, a doctoral student will be enrolled to University of Oulu Graduate School (UniOGS) doctoral program. The general requirements for admission to the UniOGS can be found at the following web pages:

Length of the position
The initial contract will be made for two (2) years including a trial period of six (6) months with a possibility of further continuation.

We expect high motivation, excellent analytical skills, and ability to achieve the pre-defined goals. The ideal applicant should hold M.Sc. degree in Computer Science, Mathematics, Physics or other technical discipline. If you have completed any of the on-line courses (e.g. on Coursera), please include it to your CV as well. This position requires prior experience in machine learning, data analysis and programming. The applicant should have excellent skills in programming as well as the ability to write efficient code. As a proof of your skills, we will appreciate Kaggle competitions medals, industrial experience and/or scientific experience (if published in high impact forums). Contributions to open-source packages, e.g. scikit-learn, Keras, PyTorch, Tensorflow are also highly valued. Despite the aforementioned requirements, the applicants with degrees in theoretical physics and pure math will also be considered. During the doctoral studies, the successful candidate is expected to publish several contributions in high impact cross-disciplinary journals, such as Scientific Reports, Medical Image Analysis, Radiology and/or computer vision conferences.

Finland is known as a country with a high quality of life and good healthcare system. The salary of the appointed researcher will be based on the demand level 2-4 chart for the teaching and research staff of Finnish universities. In addition to the basic salary, an additional salary component (not more than 50 % of the basic salary level) will be paid based on personal achievements and performance. The starting salary for a Ph.D. student is approximately 2,300 € per month and it will increase along with the progress of the student. In addition to the salary, the employed person will be insured by the university.

Application process
The application documents should include: 1)    A cover letter describing motivation to pursue a Ph.D and earlier machine learning experience 2)    Curriculum vitae and M.Sc. degree certificates 3)    Full list of peer-reviewed publications in English (if any exist). 4)    Full name and e-mail addresses of 2 referees (referees will be contacted separately). 5)    Links to your GitHub and Kaggle profile if you have those.

Applications, together with all relevant enclosures, must be submitted using the electronic application form by February 15, 2019: Applications sent by email will not be considered.

The starting date: as soon as possible. Contact details: ­­ Direct any questions or correspondence regarding the call to: Mr. Aleksei Tiulpin, Research Unit of Medical Imaging, Physics and Technology Faculty of Medicine University of Oulu, Finland E-mail:    

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Post expires on Friday February 15th, 2019