211-0865/21-2H Two PhD fellowships in Big Data in dentistry - Artificial intelligence and machine learning optimizing detection and segmentation on dental Images

Two PhD fellowships in Big Data in dentistry - Artificial intelligence and machine learning optimizing detection and segmentation on dental Images

A collaborative PhD Project in Computer Science and Dentistry

Department of Computer Science
Faculty of SCIENCE
University of Copenhagen,

and

Department of Odontology
Faculty og Health and Medical Sciences
University of Copenhagen

Department of Computer Science (DIKU) and Department of Odontology (IO) invite applicants for two PhD fellowships within the project: “Artificial Intelligence in Dentistry to optimize treatment and predict complications” which is partly financed by the UCPH Strategy 2023 pool "Data+" supporting interdisciplinary projects integrating data science with other research fields.

Start date is (expected to be) 1 March 2022 or as soon as possible thereafter.

The project

The PhD students will be developing innovative and practical AI solutions in the field of dentistry. Their  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 fields of dentistry,  dental imaging and medical image analysis. Within this collaboration, one PhD student will be employed and supervised at DIKU whereas the other will be employed and supervised at IO.  

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.

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 in dentistry.

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 fellows 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:

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.

Who are we looking for?
We are looking for candidates within the field(s) of Computer Science, Mathematics, Biomedical Engineering and dentistry with some degree of clinical experience. Excellent academic performance is expected. Publications and experience in the field of medical image analysis of AI in medicine will be of a great advantage. Proven interest and experience in clinical application of AI within dentistry wil be preferred among the candidates.

Our groups and research- and what do we offer?
Dr. Ibragimov’s group is developing AI methodology in the medical domain and applying this methodology for major clinical challenges. The group is supported by various funding sources including Novo Nordisk Foundation. For more information about the group and the research topics of interest, please consult the following webpage http://bulatibragimov.com/ . The group is part of Department of Computer Science, Section of Image Analysis, Computational Modelling and Geometry, Faculty of SCIENCE, University of Copenhagen.

The research in Dr. Bjørndal’s group is focused on finding ways to enhance treatment outcomes within deep carious pathology and endodontic treatment concepts. https://forskning.ku.dk/soeg/result/?pure=da%2Fpersons%2Flars-bjoerndal(b1651900-d544-40fa-9a3d-f0cb7d06697d)%2Fcv.html . The group is part of the Section of Oral Microbiology, Department of Cariology and Endodontics,  Faculty of Health and Medical Sciences, University of Copenhagen.

We are located in Copenhagen.

We offer creative and stimulating working conditions in dynamic and international research environment.

Principal supervisors for the two fellows are
Associate Professor, Bulat Ibragimov, Department of Computer Science, University of Copenhagen, E-mail [email protected] , Direct Phone +45 35 32 82 92.
Associate Professor, Lars Bjørndal, Department of Odontology, University of Copenhagen, E-mail [email protected] , Direct Phone +45  35 32 68 14

The PhD programme
We offer a three year full-time study within the framework of the regular PhD programme (5+3 scheme), if you already have an education equivalent to a relevant Danish master’s degree.  

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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, Mathematics, Biomedical Engineering, dentistry. 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 and SUND, 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
• Carry out dissemination and teaching activities
• 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

We are looking for the following qualifications:

• The grade point average achieved
• Professional qualifications relevant to the PhD project
• Relevant publications
• Relevant work experience either within Computer Science  or  clinical dentistry
• Other relevant professional activities
• Curious mindset with a strong interest in artificial intelligence and medical and dental imaging
• Language skills

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Application and Assessment Procedure

 Your application including all attachments must be in English and submitted electronically by clicking APPLY NOW below.

Please include: 

Application deadline:

The deadline for applications is Sunday 10 October 2021, 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 https://employment.ku.dk/faculty/recruitment-process/ .

Interviews with selected candidates are expected to be held in week 48-50

Questions
For specific information about the PhD fellowship, please contact the principal supervisors.

General information about PhD study at the Faculty of SCIENCE and Faculty of Health and Medical Sciences are available at the PhD School’s website: https://www.science.ku.dk/phd/ .

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.