PhD fellowship in Biostatistics at Section of Biostatistics, Department of Public Health

Faculty of Health and Medical Sciences
University of Copenhagen

A PhD scholarship in biostatistics with special focus on application of artificial intelligence in veterinary diagnostic imaging is available at the Section of Biostatistics, Department of Public Health, University of Copenhagen, commencing on 1 December 2020 or as soon as possible hereafter. The position is a joint position between Section of Biostatistics, Department of Public Health, the Department of Mathematical Sciences, and the Department of Veterinary Clinical Sciences, and the PhD student will be equally affiliated with all three Departments.

The PhD student is expected to develop statistical methods and algorithms that can both provide instantaneous information about equine x-rays, the image quality, and to identify regions of interest (specific joint) and determine whether a specific type of pathology is present or not.

Project description
The project will focus on a PhD project in biostatistics and data science, surrounded by two subprojects (establishment of a relevant database of equine radiographs, and dissemination and integration of experiences and knowledge from the project in the veterinary curriculum). The PhD project aims to develop AI software that replicates or assists x-ray procedures and interpretations that are routinely carried out manually by veterinary radiologists.  The student will work on three overarching topics and is encouraged and expected to drive the ideas and solutions within these three topics:

  1. Preliminary quality assessment of X-ray images. The purpose is to replicate the human process of screening an x-ray for diagnostic quality. Image quality may be marred for several reasons and we will use the newly acquired dataset to train an algorithm to immediately recognize if images are of diagnostic quality. By integrating AI and machine learning technologies at the time of data collection the hope is to improve the quality of the medical images by immediately prompting the clinician to obtain a new x-ray if needed. Also, this allows us to quantify the effect of using AI tools to improve quality of data further in the data pipeline.
  2. Feature extraction. The starting point for this topic will be to apply AI technology based on deep-learning convolutional neural networks for classification and localization of the particular osteochondral fragments. The trained algorithm is then combined with a statistical approach that extracts a score reflecting the likelihood of a structure (osteochondral fragment or other type of pathology) being present in the recorded image. Methods for evaluating the added predictive value of a new method or procedure are currently heavily debated in the statistical literature. We will develop standards for proper assessment of the added benefit of implementing new procedures based on AI technologies in veterinary and human diagnostic imaging.
  3. Identification and quantification of structures. Due to the relatively low inter- and intra-observer agreement with regards to manual identification of osteochondral fragments, automated software solutions that can improve robustness and consistency are required. This topic will focus on the benefits of using AI technologies to identify specific osteochondral fragments. The potential for improving the precision of the quantification of anatomical structures partly lies in the fact that automated software (as opposed to the radiologist) will not be limited to using one particular contrast/visual perception of the image and methods that use this information need to be developed. The method can use all possible contrasts when analyzing the x-ray in order to improve the diagnostic accuracy by the algorithm.

The research groups
The section of Biostatistics conducts general biostatistical research and methodological development in biostatistics, undertakes teaching of students at various educations, from undergraduate to postgraduate, and offers biostatistical advice to staff and students in all disciplines of the Faculty of Health Sciences. The section comprises a staff of around 35 individuals all involved with research and teaching in statistics and biostatistics at UCPH.

Department of Veterinary Clinical Sciences, Section of Medicine and Surgery provides both pre and post graduate training for veterinarians as well as advanced clinical services (including diagnostic imaging) and veterinary clinical research often with a strong translation aspect. For all purposes, the department aims to provide a clear connection between research and direct clinical applicability. The department comprises a staff around 200 individuals involved in all aspects of veterinary care, training and research.

Department of Mathematical Sciences has about 50 permanent scientific staff members; around 45 PhD students and 35 postdocs. It has strong research groups in many areas of mathematics, and active PhD, postdoc, and visitor's programs. It hosts the Data Science Laboratory with the aim of enhancing the quality of scientific data analyses in research carried out at the Faculty of Sciences.

Principal supervisor is Professor Claus Thorn Ekstrøm, Section of Biostatistics, Department of Public Health, email: ekstrom@sund.ku.dk, Phone +45 35 32 75 97. Supervisors are Professor Casper Lindegaard, Department of Veterinary Clinical Sciences, email: casper.lindegaard@sund.ku.dk, Phone +45 29916471 and Associate Professor Anders Tolver, email: tolver@math.ku.dk, Phone +45 35 32 23 37.

Start:                  1 December 2020

Duration:          3 years as a PhD student

Job description
Your key tasks as a PhD student at SUND are:

  • Carry through an independent research project under supervision 
  • Complete PhD courses or other equivalent education corresponding to approx. 30 ECTS points
  • Participate in active research environments including a stay at another research team
  • Obtain experience with teaching or other types of dissemination related to your PhD project
  • Teach and disseminate your research
  • Write a PhD thesis on the grounds of your project

Key criteria for the assessment of candidates
The successful applicant for the Ph.D. scholarship will be a statistician with a strong background in mathematics and statistics i.e., a candidate degree in for example mathematics or engineering sciences. Accordingly we require documented skills within theoretical and applied statistics as well as high-level programming. Also, the applicant should have the ability to communicate research findings in teaching, conference talks and by writing scientific papers for international journals.

It is a prerequisite that the candidate can be and is not already enrolled as a PhD student at the faculty of Health and Medical Sciences, University of Copenhagen.

Other important criteria are:

  • The grade point average achieved
  • Professional qualifications relevant to the PhD programme
  • Previous publications
  • Relevant work experience
  • Other professional activities
  • Curious mind-set with a strong interest in biostatistics, computational statistics, and image analysis.
  • Language skills

Place of employment
The place of employment is at the Section of Biostatistics, Department of Public Health, CSS, University of Copenhagen. We offer creative and stimulating working conditions in dynamic and international research environment.

Terms of employment and employment
The employment as PhD fellow is a full time and for 3 years. Starting date is 1 December 2020 or as soon as possible after.

The appointment as a PhD fellow is for 3 years. It is conditioned upon the candidate’s success­ful enrolment in the PhD school at the Faculty of Health and Medical Sciences, University of Copenhagen. This requires submission and acceptance of an application for the specific project formulated by the candidate.

The PhD study must be completed in accordance with The Ministerial Order on the PhD programme (2013) and the University’s rules on achieving the degree. Salary, pension and terms of employment are in accordance with the agree­ment between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State. Depending on seniority, the monthly salary begins around 27,590  DKK /approx. 3,700 EUR (April 2020-level) plus pension.

Questions
For specific information about the PhD scholarship, please contact the principal supervisor.

General information about PhD programs at the Faculty of Health and Medical Sciences is available at the Graduate School’s website: https://healthsciences.ku.dk/phd/guidelines/

Application procedure
Your application must be submitted electronically by clicking ‘Apply now’ below. The application must include the following documents in PDF format: 

  1. Motivated letter of application (max. one page)
  2. CV incl. education, experience, language skills and other skills relevant for the position
  3. A certified/signed copy of Master of Science certificate. If not completed, a certified/signed copy of a recent transcript of records or a written statement from the institution or supervisor will do
  4. Publication list (if possible)

Application deadline: 3 October 2020, 23.59pm CET

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 the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the hiring committee. All applicants are then immediately notified whether their application has been passed for assessment by an unbiased assessor.

The assessor makes a non-prioritized assessment of the academic qualifications and experience with respect to the above-mentioned area of research, techniques, skills and other requirements listed in the advertisement.

Once the assessment work has been completed each applicant has the opportunity to comment on the part of the assessment that relates to the applicant him/herself.

You can read about the recruitment process at https://employment.ku.dk/faculty/recruitment-process/

The applicant will be assessed according to the Ministerial Order no. 242 of 13 March 2012 on the Appointment of Academic Staff at Universities.

Interviews are expected to be held in week 47

The Faculty of Health and Medical Sciences comprises approximately 7850 students, 1700 PhD students and 4800 employees. The Faculty advances the field of health sciences through its core activities: research, teaching, knowledge sharing and communication. With basic research fields ranging from molecular studies to studies of society, the Faculty contributes to a healthy future through its graduates, research findings and inventions benefitting patients and the community. The University of Copenhagen wishes to reflect the surrounding community and invites all regardless of personal background to apply for the position. 

APPLY NOW

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

Casper Lindegaard

Contact

Claus Thorn Ekstrøm

Contact

Anders Tolver

Info

Application deadline: 03-10-2020
Employment start: 01-12-2020
Working hours: Full time
Department/Location: Department of Public Health
Content not available due to cookie preferences

You cannot see the content of this field because of your cookie preferences.

Click here to change your cookie settings.

Category: Marketing

Search all vacancies