Vacancies 68761-PhD-candidate-Artificial-Intelligence-assisted-analysis-of-CT-perfusion-in-pancreatic-cancer
  • 36 hours a week
  • Temporary
  • 3 years
  • Date of publication: 20 June 2019
  • Deadline: 2 September 2019
  • Scale 10A: max € 42220 gross per year at full employment (incl. vacation bonus and end of year payments)
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Job description

In the Netherlands approximately 2.300 patients are diagnosed with pancreatic cancer (PC) each year. PC is a devastating disease with a 5-year survival rate of only 9%, which has hardly improved in the last 40 years. In 15-20% of PC curative surgical resection is feasible. The remainder presents too late, with locally advanced disease or metastatic disease. A small group (7-32%) of patients can benefit from conventional chemo(radiation)therapy and more advanced targeted therapies, like immunotherapy. The big problem is that we cannot predict which patients will react and thus provide treatment to all. All these therapies have strong side-effects, reducing the quality of their remaining short life. Recent research indicates that it depends on the subgroups with different phenotypes and genotypes. An example of such a subtype is a vascular expression profile that exists in 35% of PCs.
 
CT perfusion (CTP) is a novel imaging method that may allow to define a quantitative vascular phenotype that can successfully select subgroups that benefit from advanced treatment. CTP is currently  limited to simple voxel perfusion parameters such as blood flow, blood volume and vascular permeability. Artificial intelligence (AI) and radiomics in particular can extract more relevant tissue features to better define a vascular phenotype of PC. CTP enhanced with radiomics can then be used to predict and monitor therapy response, facilitating personalized treatment. Data will be collected and several AI and radiomics models will be explored to best correlate CTP with immunohistological findings and clinical outcome.

During this project you will be part of the multidisciplinary pancreas working group that deals with treating patients with pancreatic cancer on a daily basis. You are also part of the Diagnostic Imaging Analysis Group (DIAG) with extensive expertise in AI, deep learning, machine learning and radiomics in medical images. The inclusion of patients and data collection has already started. Important tasks of your research project are to work out the CT perfusion and to assess the histopathological staining and to process the data in the AI model.
 
The results will also be presented at scientific conferences and lead to publications and the writing of a dissertation.

Profile

We are looking for an enthusiastic and driven researcher with the following expertise and experience:
  • Graduated in Biomedical Sciences, Data Science, Technical Medicine or equivalent studies.
  • Interest and experience in the field of imaging (CT), pathology and AI / deep learning / machine learning.
  • Scientific experience is a pre, commitment, enthusiasm and zest for work a requirement.
  • A driven and talented person who can function excellently in both groups and independently.
  • Good communication skills in Dutch and English.

Organization

The Radiology and Nuclear Medicine Department of Radboud university medical center is a dynamic department where more than 450 patients are examined and treated every day. We do this with the best and most advanced equipment available in the field of CT, MRI, Angio & Intervention radiology, Nuclear Medicine, Ultrasound and Conventional Radiology.
 
The Diagnostic Image Analysis Group (DIAG) is a research department of the Department of Radiology and Nuclear Medicine (RNG) of the Radboud university medical center. The Radboud university medical center wants to take the lead in the development of sustainable, innovative and affordable healthcare. And thus contribute to the health of people and society at home and abroad. Our mission is therefore: to have a significant impact on healthcare.
 
The research of the Radiology and Nuclear Medicine Department and DIAG is focused on the development, validation and application of new medical techniques in prostate cancer, breast cancer and also pancreatic cancer. Image analysis and machine learning play an important role in this. The success of the research group lies in the close collaboration between the clinical and research departments. About 150 researchers are currently employed.

Radboud university medical center
Radboud university medical center 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 Radboud university medical center and how you can do your part.

Employment conditions

This is a 3-year project with a full-time appointment. You will be appointed as a researcher in training with the standard salary and secondary conditions that apply to a Dutch PhD student. Your performance will be evaluated after 1 year. In the event of a positive assessment, the contract is extended by 2 years.
 
Scaling starts at € 2,357 (scale 10a) gross per month in the first year and increases to € 2,882 gross per month in the third year, with a full working week of 36 hours. In addition, we also offer an end-of-year bonus of 8.3%, an individual travel expenses budget and study options.

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 Radboud university medical center employment conditions and what our International Office can do for you when moving to the Netherlands.

Comments and contact information

All additional information about the vacancy can be obtained from John Hermans MSc MD PhD, radiologist or Henkjan Huisman MSc PhD, associate professor DIAGUse the Apply button to submit your application.

Please apply before September 2, 2019.
Recruitment agencies are asked not to respond to this job posting.

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