Improving evidence-based healthcare using artificial intelligence
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Odense M
Declaration of interest regarding PhD project: Improving evidence-based healthcare using artificial intelligence
The Research Unit for Oncology at SDU’s Department of Clinical Research would like to invite highly qualified graduates from all over the world to apply for this PhD position in radiotherapy clinical trials. The PhD student will be based at Odense University Hospital (OUH) starting as soon as possible and preferably before the end of 2022. The Danish Cancer Society and Novo support the project.
Research environment
The successful candidate’s office will be in the Laboratory of Radiation Physics, Department of Oncology at OUH. The candidate will work in a multi-disciplinary environment with medical physicists, computer scientists, medical doctors and specialised radiotherapy staff and collaborate with oncologists and medical physicists from all six Danish head and neck cancer (DAHANCA) centres.
The department has an active research environment with PhD students, associate professors and full professors. The project will be carried out in close collaboration with the DAHANCA quality assurance group and external collaborators.
Project description
Radiotherapy is given to approximately 50% of all cancer patients. The treatment relies on the interdisciplinary knowledge of radiobiology, medical physics and data science. All treatment decisions aim to be evidence-based, meaning trials have shown this treatment to be the best option. However, this is not trivial to ensure that the trial results are robust and generalisable.
The PhD project revolves around ongoing randomised clinical trials within DAHANCA and eye cancer treatment, where the aim is to use artificial intelligence (AI) to identify suboptimal treatment plans. The project will work on existing data to develop tools that can be used to validate patient treatments before the treatment starts. The AI models will look at the segmentation of medical images on both CT and MR, and develop an algorithm for dose prediction for x-rays and protons.
The candidate will start the project by formulating the project description and will have a large degree of freedom based on knowledge and interests.
Qualifications
The successful candidate will hold a master’s degree in physics, engineering, data science or related fields. Prior knowledge of clinical trials, radiotherapy, image processing and/or AI will be of high interest, and programming skills with, e.g. Matlab or python will be useful.
Fluency in English (oral and written)
For further information about the project, please contact:
PhD. Christian Rønn Hansen
Department of Oncology
Odense University Hospital
Tlf. 60688633. E-mail: [email protected]
Applications must include:
• At letter stating the interest, motivation and qualifications for the project (max. 2 pages) - upload under “Application form”.
• Detailed CV, including personal contact information
• Certified copy of diploma (Master’s degree in a relevant field)
Applications must be submitted electronically using the link “Apply online”.
Attached files must be in Adobe PDF or Word format. Each box can only contain a single file of max. 10 Mb.
Incomplete applications and applications received after the deadline will neither be considered nor evaluated. This also applies to reference letters.
Closing date 14 Nov 2022
Successful candidates will be asked to send an application to the PhD Secretariat, Faculty of Health Sciences, to be enrolled as PhD students.
The PhD programme will be carried out in accordance with Faculty regulations and the Danish Ministerial Order on the PhD Programme at the Universities (PhD order)
The terms of employment as a salaried PhD Research Fellow are stated in the Agreement between the Ministry of Finance and the Danish Confederation of Professional Associations (AC).
The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.
The Research Unit for Oncology at SDU’s Department of Clinical Research would like to invite highly qualified graduates from all over the world to apply for this PhD position in radiotherapy clinical trials. The PhD student will be based at Odense University Hospital (OUH) starting as soon as possible and preferably before the end of 2022. The Danish Cancer Society and Novo support the project.
Research environment
The successful candidate’s office will be in the Laboratory of Radiation Physics, Department of Oncology at OUH. The candidate will work in a multi-disciplinary environment with medical physicists, computer scientists, medical doctors and specialised radiotherapy staff and collaborate with oncologists and medical physicists from all six Danish head and neck cancer (DAHANCA) centres.
The department has an active research environment with PhD students, associate professors and full professors. The project will be carried out in close collaboration with the DAHANCA quality assurance group and external collaborators.
Project description
Radiotherapy is given to approximately 50% of all cancer patients. The treatment relies on the interdisciplinary knowledge of radiobiology, medical physics and data science. All treatment decisions aim to be evidence-based, meaning trials have shown this treatment to be the best option. However, this is not trivial to ensure that the trial results are robust and generalisable.
The PhD project revolves around ongoing randomised clinical trials within DAHANCA and eye cancer treatment, where the aim is to use artificial intelligence (AI) to identify suboptimal treatment plans. The project will work on existing data to develop tools that can be used to validate patient treatments before the treatment starts. The AI models will look at the segmentation of medical images on both CT and MR, and develop an algorithm for dose prediction for x-rays and protons.
The candidate will start the project by formulating the project description and will have a large degree of freedom based on knowledge and interests.
Qualifications
The successful candidate will hold a master’s degree in physics, engineering, data science or related fields. Prior knowledge of clinical trials, radiotherapy, image processing and/or AI will be of high interest, and programming skills with, e.g. Matlab or python will be useful.
Fluency in English (oral and written)
For further information about the project, please contact:
PhD. Christian Rønn Hansen
Department of Oncology
Odense University Hospital
Tlf. 60688633. E-mail: [email protected]
Applications must include:
• At letter stating the interest, motivation and qualifications for the project (max. 2 pages) - upload under “Application form”.
• Detailed CV, including personal contact information
• Certified copy of diploma (Master’s degree in a relevant field)
Applications must be submitted electronically using the link “Apply online”.
Attached files must be in Adobe PDF or Word format. Each box can only contain a single file of max. 10 Mb.
Incomplete applications and applications received after the deadline will neither be considered nor evaluated. This also applies to reference letters.
Closing date 14 Nov 2022
Successful candidates will be asked to send an application to the PhD Secretariat, Faculty of Health Sciences, to be enrolled as PhD students.
The PhD programme will be carried out in accordance with Faculty regulations and the Danish Ministerial Order on the PhD Programme at the Universities (PhD order)
The terms of employment as a salaried PhD Research Fellow are stated in the Agreement between the Ministry of Finance and the Danish Confederation of Professional Associations (AC).
The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.
Information og data
Denne ledige stilling har jobtypen "Øvrige", og befinder sig i kategorien "Øvrige stillinger".
Arbejdsstedet er beliggende i Odense M.
Jobbet er oprettet på vores service den 24.10.2022, men kan have været deaktiveret og genaktiveret igen.
Dagligt opdateret: Dette job opdateres dagligt ud fra jobudbyderens hjemmeside via vores søgemaskineteknologi og er aktivt lige nu.
- Øvrige
- Odense M
- Mandag den 14. november 2022
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