The University Medical Center Groningen (UMCG) is one of the largest hospitals in the Netherlands and the largest employer in the Northern Netherlands. In addition to providing clinical care, there is much focus on the core research, training and education. The Department of Radiology, Nuclear Medicine and Molecular Imaging is part of the UMCG. It has well-established structural international research collaborations with academic partners. At least as important as a pleasant working environment is a pleasant living environment. Groningen is a thriving university city set in quiet, spacious surroundings.

You should be a highly motivated, creative and enthusiastic researcher with an MSc degree in Computer Science, Data Science, Physics, Engineering or Biomedical Sciences or related, with a clear interest in deep learning, image analysis and an affinity with medical applications. Good communication and teamwork skills, and expertise in software development, preferably in Python/C++, are essential. Experience with artificial intelligence is a pre. The research should result in a PhD thesis.

The UMCG has a preventive Hepatitis B policy. The UMCG can provide you with the vaccination, should it be required for your position.

In case of specific professions a ‘Certificate of Good Conduct’ is required.

Your salary will be a minimum of € 2.495,- gross per month in the first year and a maximum of € 3.196,- (scale PhD) in the final (4th) year, based on a full-time appointment. In addition, the UMCG will offer you 8% holiday pay, and 8.3% end-of-year bonus.
The conditions of employment comply with the Collective Labour Agreement for Medical Centres (CAO-UMC). English: http://www.nfu.nl/english/about-the-nfu/

More information
For more information about this vacancy please contact:
- Dr. Derya Yakar, telephone number: +31 50 361 4263 / +31 50 361 3113, e-mail address: d.yakar@umcg.nl
- Dr. Thomas Kwee, telephone number: +31 50 361 4263 / +31 50 361 3113, e-mail address: t.c.kwee@umcg.nl
- Dr. Henk Jan Huisman, telephone number: +31 24 361 7536, e-mail address: henkjan.huisman@radboudumc.nl

Applications
The following should be included: CV, list of followed courses and grades, letter of motivation, and preferably a reprint or link to your Master thesis and publications in English you have written.

Radiology, Nuclear Medicine & Medical Imaging

One million men receive a prostate cancer diagnosis, and three hundred thousand die from prostate cancer each year worldwide. Magnetic Resonance Imaging (MRI) represents a major breakthrough by accurately detecting clinically significant prostate cancers at an early, potentially more curable stage. The same MRI can also be used for guiding targeted treatments and for avoiding unnecessary systematic biopsies. This excellent clinical value has led to a recent change of national and European guidelines which at present recommend MRI as first-line diagnostic work up in all patients suspected of PCa. As a consequence, this will lead to an increasing demand for Prostate MRI and associated costs. In this project, FastMri, the aim is to develop new artificial intelligence (AI) techniques that will make MRI faster and at the same time more accurate. Specific emphasis will be put on developing fast MRI sequences in the fields of detection and targeted therapies with the help of k-space undersampling and steering methods. Eventually leading to innovative harmoniously operating AI techniques together with corresponding MRI sequence development. The main purpose of this PhD is the design and development of novel methods that speed up MRI acquisition while retaining diagnostic performance. Results will be presented at international scientific meetings and published in international peer reviewed journals.

The different partners involved in FastMRI are the UMCG, the Diagnostic Image Analysis Group (DIAG) of the Radboud University Medical Center Nijmegen, the faculty of Science & Technology of the University of Twente, and Siemens Healthineers.

The FastMri collaboration project is co-funded by the PPP Allowance made available by Health Holland, Top Sector Life Sciences & Health, to stimulate public-private partnerships and by Siemens Healthineers.