Postdoc in Deep Learning for Medical Image Segmentation

Updated: 10 months ago
Job Type: FullTime
Deadline: 09 Jun 2023

The Department of Clinical Medicine at Faculty of Health at Aarhus University invites applications for a position as Postdoc in the field of Deep Learning for Medical Image Segmentation as per 1 October 2023 or as soon as possible thereafter. The position is a fixed-term 2 year full-time position.

As a postdoc at the Department of Clinical Medicine, you will be part of what is probably the largest health science research department in Denmark. Our clinical research covers all the medical specialities and takes place in close collaboration with the university hospital and the regional hospitals in the Central Denmark Region. We have approx. 30,000 square metres of modern research facilities for experimental surgery and medicine, animal facilities and also advanced scanners at our disposal. The department has overall responsibility for the Master's degree programs in medicine and in molecular medicine. At the department we are approx. 670 academic employees, 500 PhD students and 160 technical/administrative employees who are cooperating across disciplines. You can read more about the department here and about the faculty here .

You will be working at the Danish Center for Particle Therapy (DCPT), Aarhus University Hospital. The research staff at DCPT currently includes five professors in medical physics, three associate professors and approximately 40 PhD students and postdocs primarily funded by external grants, contributing to the research environment at DCPT. There is a close collaboration with the neighboring Department of Oncology.

About the research project
The position will be part of the project “Reconstructing uncertainty into an operational tool in AI based auto-segmentation of medical images”, which is funded by Aarhus University Research Foundation under supervision of principal investigator Professor Stine Korreman.
The project aims to quantify the segmentation uncertainty of deep learning prediction of tumours and organs-at-risk in head and neck cancer, including categorization of types of uncertainty based on pattern of appearance combined with image feature analysis. Uncertainty estimations can be compared with actual deviations in a large clinical test data set, for performance assessment with respect to capability of detecting potential model prediction errors. The objective is to develop tools enabling transparency of AI predictions, which can help clinicians assess the validity of model results, decrease risk of failures, and increase clinicians’ confidence in the models.  

Your job responsibilities
As Postdoc in Deep Learning for Medical Image Segmentation, your position is primarily research-based but may also involve teaching assignments. You will contribute to the development of the department through research of high international quality. In your daily work, you will work closely with colleagues on your project, where you will receive supervision and guidance.

Your main tasks will consist of:

  • Independent research of high international quality, including publication.
  • Collaboration with and co-supervision of PhD student in the project.
  • Collaboration with overall research group on artificial intelligence in radiation oncology.
  • Participation in local journal club and seminar series.
  • Contributing to maintenance and planning of use of the high-performance GPU cluster at DCPT.

You will report to the Professor Stine Sofia Korreman

Your competences
You have academic qualifications at PhD level, preferably within medical physics, statistics, biomedical engineering or computer science, with focus on medical image analysis and/or machine learning. Medical doctors with strong computational skills may also be considered for the position. Furthermore, the following competences will be expected:

  • Fluency in English (oral and written).
  • Programming skills (Python, and/or C# or similar programming language).
  • Analytical skills and ability to work independently on a project basis.
  • Prior experience in radiation oncology will be considered an advantage.

As a person, you have good interpersonal skills, are inclusive and team-oriented and able to contribute to a good work environment. We expect you to be fluent in oral and written English.

In order to be assessed as qualified for a Postdoc position, you must meet these academic criteria .

Questions about the position
If you have any questions about the position, please contact Professor Stine Sofia Korreman, +45 2811 9886.

Your place of work will be the Department of Clinical Medicin Danish Center for Particle Therapy, Aarhus University Hospital, Palle Juul-Jensens Boulevard 25, DK-8000 Aarhus C, Denmark.

We expect to conduct interviews in the week of July 3-7 2023.



Terms of employment


Application

Your application must include the following:

  • Motivated application
  • Curriculum Vitae
  • Diploma
  • Template for applicant - postdoc
  • A list of publications
  • A teaching portfolio. We refer to Guideline on the use of teaching portfolios
  • A maximum of five of the publications of greatest relevance to the job may be submitted (optional)
  • Research plan can be uploaded (optional)
  • Coauthor statement(s) can be uploaded (optional)
  • References/recommendations can be uploaded separately in the e-recruitment system (optional)

We refer to the faculty’s

Guidelines for applicants

.

The assessment committee may decide to include non-submitted material in its statement. In such cases, you will be informed and obliged to submit material, unless your application is withdrawn.

Aarhus University’s ambition is to be an attractive and inspiring workplace for all and to foster a culture in which each individual has opportunities to thrive, achieve and develop. We view equality and diversity as assets, and we welcome all applicants.


Letter of reference

If you want a referee to upload a letter of reference on your behalf, please state the referee’s contact information when you submit your application. We strongly recommend that you make an agreement with the person in question before you enter the referee’s contact information, and that you ensure that the referee has enough time to write the letter of reference before the application deadline.

Unfortunately, it is not possible to ensure that letters of reference received after the application deadline will be taken into consideration.



International applicant?

Aarhus University offers a broad variety of services for international researchers and accompanying families, including assistance with relocation and career counselling to expat partners. Please find more information about the International Staff Office and the range of services

here

. Aarhus University also has a Junior Researcher Association and offers career development support. You can read more about these resources

here

.

The application must be submitted via Aarhus University’s recruitment system, which can be accessed under the job advertisement on Aarhus University's website.



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