BEMÆRK: Ansøgningsfristen er overskredet
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.
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.
Ansættelsesgrundlag
- Ansættelse som postdoc. forudsætter videnskabelige kvalifikationer på ph.d.-niveau.
- Ansættelsesproceduren er yderligere beskrevet i ministeriets Bekendtgørelse om ansættelse af videnskabeligt personale ved universiteter.
- Ansættelse sker i henhold til overenskomst for akademikere i staten.
- Aflønning sker i overensstemmelse med ovenstående og Lønkatalog for medarbejdere ved Health.
- Kvalifikationskrav og stillingsindhold er yderligere beskrevet i stillingsstruktur for videnskabeligt personale ved universiteter.
Ansøgning
Din ansøgning skal indeholde følgende:
- Ansøgning
- Curriculum Vitae
- Eksamensbevis
- Skabelon til ansøger – postdoc
- Publikationsliste
- Undervisningsportfolio. Vi henviser til Vejledning til anvendelse af undervisningsportfolio
- Op til 5 af de for stillingen mest relevante publikationer kan medsendes (valgfrit)
- Forskningsplan kan medsendes (valgfrit)
- Medforfattererklæring kan medsendes (valgfrit)
- Referencer/anbefalinger kan uploades særskilt i e-rekrutteringssystemet (valgfrit)
Bedømmelsesudvalget kan beslutte at efterspørge ikke indsendt materiale i bedømmelsen. I så fald kontakter vi dig, og du vil være forpligtet til at indsende materiale, medmindre din ansøgning trækkes tilbage.
Aarhus Universitet vil være en attraktiv og inspirerende arbejdsplads for alle og ønsker en kultur, hvor hver enkelt kan udfolde og udvikle sig. Vi ser ligestilling og diversitet som en styrke og opfordrer derfor alle interesserede til at ansøge.
Referencer
Hvis du ønsker, at en referenceperson skal uploade et referencebrev på dine vegne, så angiv venligst referencepersonens kontaktoplysninger, når du indsender din ansøgning. Vi anbefaler, at du laver en aftale med den pågældende, inden du indtaster referencepersonens kontaktoplysninger, og at du sikrer, at referencepersonen har tid nok til at skrive referencebrevet inden ansøgningsfristen.
Det er desværre ikke muligt at sikre, at referencebreve indgivet efter ansøgningsfristens udløb bliver taget i betragtning.
International ansøger?
Aarhus Universitet tilbyder en bred vifte af services til internationale forskere og ledsagende familier, herunder relocation service og karrierevejledning til medfølgende partnere. Find mere information om at ankomme til og arbejde i Danmark her. Aarhus Universitet tilbyder også karriereudviklingsprogrammet, Junior Researcher Development Programme. Du kan læse mere om det her.
Ansøgning sendes via Aarhus Universitets rekrutteringssystem, som kan tilgås under stillingsopslaget på Aarhus Universitets hjemmeside.
Om Aarhus Universitet
Aarhus Universitet er et fagligt bredt og forskningsintensivt universitet med høj kvalitet i uddannelse og forskning, og et stærkt engagement i samfundsudviklingen nationalt og globalt. Universitetet tilbyder et inspirerende uddannelses- og forskningsmiljø for 38.000 studerende og 8.300 medarbejdere med en årlig omsætning på 7,0 mia. kr. Læs mere på www.au.dk
INFORMATIONER OM STILLINGEN:
- Arbejdspladsen ligger i:
Aarhus Kommune
-Virksomheden tilbyder:
-Arbejdsgiver:
Aarhus Universitet, Vennelyst Boulevard 9, 8000 Aarhus C
-Ansøgning:
Ansøgningsfrist: 09-06-2023; - ansøgningsfristen er overskredet
Ved skriftlig henvendelse: https://AU.emply.net/recruitment/vacancyApply.aspx?publishingId=da46cac1-1a29-457b-879a-31629a335248
Se mere her: https://job.jobnet.dk/CV/FindWork/Details/5842241
