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We are looking for an enthusiastic researcher that is eager to collect and analyze clinical patient data with the ultimate purpose to improve our clinical patient care and help to answer the question: How should we create the best possible radiotherapy treatment plan with minimized risks of long-term side effects ?
In this PhD project we aim at developing adequate prediction models for toxicity risks after hypofractionated radiotherapy for prostate cancer, and translate these into optimal treatment solutions. Hypofractionation using advanced radiotherapy techniques and online imaging has become the new standard in radiotherapy for prostate cancer. At the same time, prediction models used for treatment optimization strategies are still unchanged and based on data collected with standard fractionation. To develop accurate models for the clinic will be of great importance to limit toxicity risks for each patient as much as possible. Data of an ongoing prospective cohort study will be used to develop these models; also data from other institutes will be used to validate these models.
You will work in a multi-disciplinary team of radiation oncologists, medical physicists, data managers, and translational researchers at a world leading university medical center. You will handle databases, help with documentation of side effects, analyze data, develop prediction models and investigate their impact on optimized dose, write and publish manuscripts, and report results at local meetings and at (inter-) national conferences.
This project, "Hypofractionated radiotherapy for prostate cancer: towards evidence-based best practice with state-of-the art normal tissue complication models - HYPROSTAR", is a collaboration between the Erasmus Medical Center and other Dutch radiotherapy institutes, and is funded by KWF (Dutch Cancer Society) for a period of 4 years.
Erasmus MC (University Medical Center Rotterdam)
You are a highly motivated candidate with a master degree related to Medical Physics, Biomedical Sciences, Health Sciences, Medicine, Epidemiology, or similar. Excellent skills in database handling, statistical analyses and epidemiological methods are required, as well as in academic writing and presenting in English. As you will be part of a multidisciplinary team, good communication skills are essential. You are eager to learn and you are comfortable working in an academic research environment. Research experience in either oncology, urology, medical physics, modeling, and/or radiotherapy is a plus.
Conditions of employment
- You will receive a temporary position for 4 years. The gross monthly salary is € 2.631 ,- in the 1st year and increases to € 3.336,- in the 4th year (scale OIO), based on a full-time working week of 36 hours.
- Excellent fringe benefits, such as a 13th month that is already paid out in November and an individual travel expense package.
- Pension insurance with ABP, we take care of approximately 2/3 of the monthly contribution.
- Special benefits, such as an incompany physiotherapist and bicycle repairer. There is also a gym where you can work on your fitness after work.
The PhD candidate will be positioned at the Department of Radiotherapy of the Erasmus MC Cancer Institute. We use the latest technologies and treatments to maximize the chances of finding a cure. Intensive collaboration among experts at our institute ensures that improved treatments will become quickly available for our patients. For each type of cancer, specialists work closely together to provide the best possible personalized care. Together we know more, we can do more, and we can achieve more. The department of Radiotherapy is one of the largest in the Netherlands and comprises a very active and strong international research program and a large research group of Postdocs, PhD students, and Master students. It has a wide-ranged and internationally renowned research program varying from fundamental and translational radiobiology, to biological image guided, interventional and adaptive radiotherapy and clinical trials. All research is focused on improving clinical practice and has led to groundbreaking innovation such as fully automated treatment planning and daily treatment plan selection strategies. The department has its own outcome unit that supports (clinical) research including data management.