Vacancy: PhD candidate ‘MRI-based decision support tool for chronic low back pain’

  • 36 hours a week
  • Temporary
  • 4 years
  • Date of publication: 16 September 2019
  • Deadline: 7 October 2019
  • Scale 10A: max € 43305 gross per year at full employment (incl. vacation bonus and end of year payments)

Please go to the original vacancy post on the Radboudumc website and use the “apply to job” button to submit your application.

Job description

Chronic low back pain (CLBP) is a highly prevalent condition with poorly understood etiology. The affected population is heterogeneous and the condition multifactorial. This makes it challenging to determine the right treatment. Within the Radboud AI for Health lab, we are offering a PhD position for developing an innovative MRI-based decision support tool to help physicians and patients in choosing a treatment that is likely to be successful.

The PhD candidate will contribute to this decision support tool by developing automatic image analysis methods for assessing degenerative spinal and muscular changes on MRI cans. These image analysis methods will be based on deep learning and similar state-of-the-art technologies. Next to the development of image analysis methods, the candidate will also contribute to the validation of algorithms and decision support tool and their integration into clinical routine.

The project is a close collaboration between clinicians, including orthopedic surgeons and radiologists, and image analysis, machine learning, and clinical health scientists. The PhD candidate will work at the Department of Orthopaedics and in the Diagnostic Image Analysis Group (DIAG) at the Department of Radiology and Nuclear Medicine. We are additionally collaborating in this project with the Sint Maartenskliniek, a hospital specialized in musculoskeletal disorders in which every year thousands of patients with chronic low back pain are examined and treated by the orthopedic spine surgeons.

Profile

We are looking for an ambitious, creative and enthusiastic computer scientist, biomedical engineer or data scientist who would like to contribute to innovative diagnostics and decision support in the clinical field.

Good communication skills are a prerequisite to facilitate and coordinate the interdisciplinary collaboration.

You should have a MSc degree in a related field, such as biomedical engineering or technical medicine, and a clear interest in medical image analysis and machine learning. Programming experience, preferably in Python, and a good command of the English language are essential. Experience with machine learning, medical image processing and biostatistical modeling is a plus.

Organization

The Radboud University Medical Center is a leading academic center for healthcare, medical science and education with almost 11,000 employees and over 3,000 students. The hospital collaborates with the Radboud University Nijmegen in the Radboud AI for Health lab, an Innovation Center for Artificial Intelligence (ICAI) lab, to solve clinical problems with innovative use of artificial intelligence.

Radboudumc

Radboudumc strives to be a leading developer of sustainable, innovative and affordable healthcare to improve the health and wellbeing of people and society in the Netherlands and beyond. This is the core of our mission: To have a significant impact on healthcare. To get a better picture of what this entails, check out our strategy.

Read more about what it means to work at Radboudumc and how you can do your part.

Employment conditions

Upon commencement of employment we require a certificate of conduct (Verklaring Omtrent het Gedrag, VOG) and there will be, depending on the type of job, a screening based on the provided cv. Radboud university medical center’s HR Department will apply for this certificate on your behalf.

Read more about the Radboudumc employment conditions and what our International Office can do for you when moving to the Netherlands.

Comments and contact information

In your application include a motivation letter, your CV, list of grades and links to publications, your Master thesis or other work you have written in English.

An assessment can be a part of the selection procedure.

All additional information about the vacancy can be obtained from Dr. Nikolas Lessmann (Nikolas.Lessmann@radboudumc.nl), Diagnostic Image Analysis Group or from Dr. Miranda van Hooff (Miranda.vanHooff@radboudumc.nl), Department of Orthopedics.

Please go to the original vacancy post on the Radboudumc website and use the “apply to job” button to submit your application.

Please apply before October 7, 2019.

Recruitment agencies are asked not to respond to this job posting.



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