PhD Fellowship in Big Data in Dentistry
University of Copenhagen Department of Odontology
Denmark

PhD fellowship in Big Data in dentistry - Artificial intelligence and machine learning optimizing detection and segmentation on dental X-rays

Department of Odontology

Faculty of Health and Medical Sciences

University of Copenhagen

A PhD fellowship is offered at Department of Odontology commencing on February 1st 2021 or as soon as possible.

The PhD student will be developing innovative and practical AI solutions in the field of dentistry. His/her particular responsibilities will be the analysis and pre-processing of dental X-rays, the development of an AI-based algorithm for the segmentation of dental structures, and validation using clinical data from the Department of Odontology. Results have the potential to be published in top journals in the field of dental imaging and medical image analysis.

Project description

Artificial Intelligence (AI) and machine learning have huge potential for dentistry, but have been used only in a few studies so far.

High precision data can be beneficial for general dental practice and for society as a whole. Merging dental data with other medical databases could provide a complete and individual health profile prior to treatment. AI can provide an immediate validated state-of-the-art interpretation of potential signs of diseases that can inform dentists during examination, diagnostics and treatment planning.

Big Data is a central theme in the research strategy at the Department of Odontology.

The project is based on the electronic patient file system used at the Department of Odontology, which includes at least 1.5 million digital X-rays, patient data from 270,000 persons and high-quality clinical images covering a 10-year period of patient flows. These unique data are ideal for the application of AI and machine learning in order to improve pre-, intra- and post-treatment data. This project will focus on dental variables on x-rays specifically within the field of cariology (decayed teeth) and endodontics (root treatments) and it will form part of a larger collaborative project covering Big Data.

The objectives of the PhD project include extraction of relevant x-ray images, optimizing the images for further data analyses (conversion and pre-processing) as well as labelling dental variables for pathological conditions and sequelae (i.e. carious lesion depths, presence of apical periodontitis, restoration outlines and root fillings). Identical procedures will cover key anatomical landmarks.

The PhD fellow will be expected to participate in the development and use of an artificial deep neural network for automatic segmentation of x-rays of healthy teeth vs. teeth with pathological conditions.

The overall objectives of the project:

  1. Create new information by the development of algorithms to analyse x-rays and clinical data
  2. Contribute to better personalized treatment (precision medicine)
  3. Reduce the number of suboptimal dental treatments.

It is expected that a successful application of AI on dental data will provide an interactive platform enhancing the decision process in general dental practice.

Supervision

The project will be carried out under the supervision of:

  • Principal supervisor: Associate Professor PhD,  Dr Odont, DDS Lars Bjørndal, Department of Odontology, University of Copenhagen, Cariology and Endodontics.
  • Primary co-supervisor: Tenure Track Assistant Professor, PhD, Bulat Ibragimov, DIKU.
  • Additional co-supervisor: Associate Professor PhD, DDS, Azam Bakhshandeh, Department of Odontology, University of Copenhagen, Cariology and Endodontics.

Qualifications

The candidate must hold a Master’s degree of Computer Science and must document skills in image analysis, machine learning, and Python programming language. Experience working with dental x-rays, medical images and machine learning-based clinical decision making will be a great advantage.

It is a prerequisite that the candidate can be enrolled as a PhD student at the Faculty of Health and Medical Sciences.

Terms of employment

The employment is for a 3-year period, and full time (37 hrs/week). A stipend will cover the salary and standard courses for the 3-year period.

Salary and other terms and conditions of appointment are set in accordance with the Agreement between the Ministry of Finance and AC (Danish Confederation of Professional Associations). The candidate is required to perform assigned tasks in connection with teaching etc. up to 840 work hours during the period of employment.

Questions

For further information regarding the position, please contact Associate Professor Lars Bjørndal labj@sund.ku.dk

Application and deadline

The application must include:

  • Cover letter (motivation for applying including a description of the applicant’s research profile)
  • Curriculum Vitae
  • Diploma and transcripts of records (collated into 1 file)
  • List of publications
  • Other relevant documents/information

The application must be sent electronically by clicking on the link below.

After the deadline, the authorized recruitment manager selects applicants for assessment on the advice of the Appointments Committee. Applicants are notified whether their application has been passed for assessment by an expert assessment committee. Selected applicants are notified of the composition of the committee and each applicant has the opportunity to comment on his/her assessment. You may read about the recruitment process at http://employment.ku.dk

Candidates who are already enrolled as PhD students at the Graduate School of Health and Medical Sciences cannot apply for this position.

The closing date for applications is 25th October 2020

The University of Copenhagen encourages all interested in this post to apply.

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Part of the International Alliance of Research Universities (IARU), and among Europe’s top-ranking universities, the University of Copenhagen promotes research and teaching of the highest international standard. Rich in tradition and modern in outlook, the University gives students and staff the opportunity to cultivate their talent in an ambitious and informal environment. An effective organisation – with good working conditions and a collaborative work culture – creates the ideal framework for a successful academic career.

Contact

Lars Bjørndal
E-mail: labj@sund.ku.dk

Info

Application deadline: 25-10-2020
Employment start: 01-02-2021
Working hours: Full time
Department/Location: Department of Odontology


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