Postdoc deep learning for medical image analysis in radiotherapy
We have shown in several publications that image features in medical images of head and neck cancer patients are related to treatment outcome and to the risk …
- Hanzeplein, Groningen, Groningen
- Tijdelijk contract / Tijdelijke opdracht
We have shown in several publications that image features in medical images of head and neck cancer patients are related to treatment outcome and to the risk on complications after radiotherapy. In this project the added value of using deep learning techniques to identify prognostic and predictive image features will be explored. Deep learning algorithms will be developed and optimized for this purpose in cooperation with the project partner COSMONIO (https://cosmonio.com). Methods will be developed and validated based on clinical data from the UMCG and the German partner Pius Hospital Oldenburg. After validation those methods can be used to optimize the radiotherapy treatment of individual patients.
- Excellent researcher with PhD in (Applied) Physics, Technical Medicine, Biomedical Engineering, Computer Science or related discipline.
- Experienced in programming preferably in Python and C++.
- Experience with machine learning, deep learning, clinical modeling, diagnostic imaging, radiotherapy and DICOM data.
- Excellent team player, thorough in documentation, clear in communication.
- Affinity with research and medicine.
- Fluent in English and/or Dutch.
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 Behaviour’ is required.
Conditions- Fulltime position (36 hours) at the UMCG for a maximum of three years, starting 3rd quarter 2018.
- Your salary dependent on qualifications and work experience up to a maximum of € 4.216,- (scale 10) gross per month for a fulltime position.
- The UMCG will offer you 8% holiday allowance, 8,3% end of the year bonus and a development budget.
- Conditions of employment are according to the Collective Labour Agreement for Medical Centers (CAO-UMC).
- Assistance in obtaining housing is possible.
Marianna Sijtsema, PhD, Medical Physicist, Department of Radiation Oncology
Phone +31-621102076 / +31 50 3613674 (secretariat), e-mail: email@example.com (please do not use for applications).
Peter van Ooijen, PhD, Medical Informatics, Center for Medical Imaging (CMI)
Phone +31 50 361 2286, e-mail: firstname.lastname@example.org (please do not use for applications)
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