Ongeveer 18 uur geleden - Technische Universiteit Eindhoven - Eindhoven
PhD-student for our research division Knowledge Engineering / Data Science
The radiotherapy institute MAASTRO CLINIC provides cancer care to patients in the Limburg region of the Netherlands. MAASTRO CLINIC works closely with the …
- Dr Tanslaan, Maastricht, Limburg
- Tijdelijk contract / Tijdelijke opdracht
- Uren per week:
- 36 uur
- € 2336 per maand
The radiotherapy institute MAASTRO CLINIC provides cancer care to patients in the Limburg region of the Netherlands. MAASTRO CLINIC works closely with the University and University Hospital Maastricht (MUMC+) in the fields of education, clinical and pre-clinical research. MAASTRO CLINIC and MUMC+ work together in ZON-PTC, the South-East Netherlands center for proton radiotherapy.
MAASTRO’s strategic goal is to deliver personalized cancer treatments by applying advanced medical technology and scientific research.
For one of our research divisions, the division of Knowledge Engineering, we are looking for a: PhD-student (36 hours/week)
The research division MAASTRO Knowledge Engineering focuses on data & computer science research in three interlocking themes:
- The development of global data sharing infrastructures for routine cancer care data;
- The learning of cancer outcome prediction models from routine care data;
- The application in clinical practice of cancer outcome prediction models to improve routine care.
In theme 3, we aim to implement the research we do in the other two themes directly in the clinic, where possible. For this, we closely collaborate with our physicians, physician assistants, datamanagers and medical physicists. PROSPECT is one of these implementation projects and aims to develop a web-based tool that enables patients and doctors to make informed treatment decisions.
We are looking for a PhD-student that is interested in translational research on the clinical implementation of innovative data science. You will be part of the MAASTRO Knowledge Engineering team consisting of computer scientists, medical physicists and medical informaticists, PhD students, software engineers and post-doctoral researchers. You will be involved in multiple funded research projects in theme 3 where IT, data infrastructure and shared decision making come together. You will build machine learning models on clinical and imaging data and you will work together with software developers, patients and doctors to create IT tools for clinical use.
To fit this position, you have:
- A Master's degree in data science, computer science, machine learning (or comparable);
- Expertise in machine learning and experience in working in a health care setting;
- Experience or interest in health care, shared decision making or omics;
- Excellent language skills in English;
- Willingness to travel globally and be away from home for extended periods (up to 3 months);
- Good written and verbal communication skills and the ability to work in a multidisciplinary team.
Conditions of employment and salary are based on the Dutch Collective Labour Agreement for Hospitals (CAO-Ziekenhuizen). You will receive a fulltime contract (36 hours/week) for an initial period of one year. Your salary will be according to the salary scale FWG 50 (starting with € 2.336,- depending on your relevant experience). Within the collective labor agreement, there is an extensive package of fringe benefits, including a good pension arrangement, a 8.33% holiday allowance and end-of-year bonus and an excellent pension provision. In addition, MAASTRO offers various discount schemes with regard to (healthcare) insurance, bicycle purchase and sports subscriptions.
Do you want to know more about this position? Further information will be gladly provided by Prof. dr. ir. André Dekker (firstname.lastname@example.org) or dr. Rianne Fijten (email@example.com). Both can also be reached by telephone number: +31-(0)88 44 55 666.
Interested in this position? You can apply until February 14th 2019 by uploading your motivation letter and curriculum vitae via the 'Apply' button.