BEMÆRK: Ansøgningsfristen er overskredet
PhD fellowship in medical image analysis
Department of Computer Science
Faculty of SCIENCE
University of Copenhagen
The IMAGE section at the Department of Computer Science invites applicants for a PhD fellowship in self-supervised machine learning methods for large scale analysis of medical longitudinal images. The project is part of a larger research project entitled Self-supervised artificial intelligence for large scale analysis of longitudinal images in oncology, which is financed by the Independent Research Fund Denmark.
Start date is (expected to be) 1st of October 2023 or as soon as possible thereafter.
The project
Machine learning and in particular deep learning (DL) have the potential to change how images are interpreted and processed in medicine. Most DL systems learn to solve problems in a supervised manner directly from examples of input and output and often many manually labeled examples of output are needed to get to a satisfactory performance. Unfortunately, abundance of data is rare in medical imaging, instead, what is often available is a limited number of simply labeled scans from a single study/institution severely limiting supervised learning. Gathering large amounts of unlabeled data is easier. Images gathered during cancer treatment and specifically radiotherapy is an excellent source of such unlabelled data because multiple images and multiple imaging modalities are used for diagnostics, treatment planning, treatment delivery, and finally follow-up. This becomes dozens of 3D scans for each patient and tens of thousands per year per radiotherapy center.
This project is focused on learning from combinations of such labeled and unlabeled medical imaging data, with unsupervised and semi-supervised learning and so-called self-supervised techniques. Self-supervised methods are state of the art in a number of computer vision problems and language models that learn unsupervised and semi-supervised are currently changing society through language processing, but have so far not found wide adoption in the medical imaging domain. The PhD project goals are to investigate the learning and scaling potential of existing and developed methods and investigate their benefits for analysis of longitudinal images by using the large amounts of oncology imaging data available in hospital databases. This could potentially have wide impact on medical image analysis and processing, however, the PhD project will also run side-by-side with a medical PhD project at the Department of Oncology at Rigshospitalet, which aims to use the results of the method development and analysis to specifically improve risk modelling of tumor recurrence and side-effects after treatment.
Who are we looking for?
We are looking for candidates within or related to the field(s) of computer science, physics, or mathematics. To be eligible to apply for these positions, applicants need to have or be about to obtain an MSc degree in one of these fields (education level options are discussed further below). In addition, the ideal candidate might have
- solid programming experience
- experience in image analysis and machine learning / deep learning
- a wish to apply advanced computer science and machine learning techniques in medicine
- a creative, solution oriented mindset and able to work both independently and in research teams
- relevant publications
- relevant work experience
- other relevant professional activities
- good language skills, the group is international and fluency in spoken and written English is a requirement
Our group and research- and what do we offer?
The project will be carried out at and is part of an existing cross-disciplinary collaboration between the Image Analysis, Computational Modelling, and Geometry (IMAGE) section at the Department of Computer Science, Faculty of Science, University of Copenhagen and the Radiotherapy Research group at the Department of Oncology, Rigshospitalet. The collaboration aims to combine state of the art image analysis and machine learning tools, expertise, and computational resources with state of the art radiation therapy equipment, knowhow, and large clinical databases recording treatment data and outcomes from one of the largest European radiotherapy departments. Both involved research groups are relatively large, diverse and internationally renowned, each consisting of more than 20 PhDs and Postdocs.
The project will be co-supervised by Professor Ivan Richter Vogelius from the Department of Oncology at Rigshospitalet.
Principal supervisor is Associate Professor Jens Petersen from the Department of Computer Science, University of Copenhagen. E-mail: phup@di.ku.dk, Direct Phone: +45 60687733.
The PhD programme
The PhD programme is a three year full-time study within the framework of the regular PhD programme (5+3 scheme). An education equivalent to a relevant Danish master’s degree is a requirement.
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Getting into a position on the regular PhD programme
Qualifications needed for the regular programme
To be eligible for the regular PhD programme, you must have completed a degree programme, equivalent to a Danish master’s degree (180 ECTS/3 FTE BSc + 120 ECTS/2 FTE MSc) related to the subject area of the project, e.g. computer science, physics, mathematics. For information of eligibility of completed programmes, see General assessments for specific countries and Assessment database.
Terms of employment in the regular programme
Employment as PhD fellow is full time and for maximum 3 years.
Employment is conditional upon your successful enrolment as a PhD student at the PhD School at the Faculty of SCIENCE, University of Copenhagen. This requires submission and acceptance of an application for the specific project formulated by the applicant.
The terms of employment and salary are in accordance to the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State (AC). The position is covered by the Protocol on Job Structure.
Responsibilities and tasks in both PhD programmes
- Carry through an independent research project under supervision
- Complete PhD courses corresponding to approx. 30 ECTS / ½ FTE
- Participate in active research environments, including a stay at another research institution, preferably abroad
- Teaching and knowledge dissemination activities
- Write scientific papers aimed at high-impact journals
- Write and defend a PhD thesis on the basis of your project
Application and Assessment Procedure
Your application including all attachments must be in English and submitted electronically by clicking APPLY NOW below.
Please include:
- Motivated letter of application (max. one page)
- Your motivation for applying for the PhD project
- Curriculum vitae including information about your education, experience, language skills and other skills relevant for the position
- Original diplomas for Bachelor of Science or Master of Science and transcript of records in the original language, including an authorized English translation if issued in another language than English or Danish. If not completed, a certified/signed copy of a recent transcript of records or a written statement from the institution or supervisor is accepted.
- Publication list (if possible)
The deadline for applications is 9 July 2023, 23:59 GMT +2.
We reserve the right not to consider material received after the deadline, and not to consider applications that do not live up to the abovementioned requirements.
The further process
After deadline, a number of applicants will be selected for academic assessment by an unbiased expert assessor. You are notified, whether you will be passed for assessment.
The assessor will assess the qualifications and experience of the shortlisted applicants with respect to the above mentioned research area, techniques, skills and other requirements. The assessor will conclude whether each applicant is qualified and, if so, for which of the two models. The assessed applicants will have the opportunity to comment on their assessment. You can read about the recruitment process at http://employment.ku.dk/faculty/recruitment-process/.
Interviews with selected candidates are expected to be held during week 33, however, to allow for possible summer holidays of qualified candidates we may deviate from this.
Questions
For specific information about the PhD fellowship, please contact the principal supervisor.
General information about PhD study at the Faculty of SCIENCE is available at the PhD School’s website: https://www.science.ku.dk/phd/.
The University of Copenhagen wishes to reflect the surrounding community and invites all regardless of personal background to apply for the position.
INFORMATIONER OM STILLINGEN:
- Arbejdspladsen ligger i:
Lyngby-Taarbæk Kommune
-Virksomheden tilbyder:
-Arbejdsgiver:
KU - SCIENCE - DATALOGISK INSTITUT - UP1, Universitetsparken 1, 2100 København Ø
-Ansøgning:
Ansøgningsfrist: 09-07-2023; - ansøgningsfristen er overskredet
Ved skriftlig henvendelse: https://candidate.hr-manager.net/ApplicationInit.aspx?cid=1307&ProjectId=159482&DepartmentId=18970&MediaId=4632&SkipAdvertisement=true
Se mere her: https://job.jobnet.dk/CV/FindWork/Details/5850848