PhD Candidate in Machine Learning / Deep Learning for Medical Imaging Purposes
|Published||March 9, 2023|
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About the job
For a position as a PhD Candidate, the goal is a completed doctoral education up to an obtained doctoral degree.
The Department of Computer Science (IDI) will now employ a Ph.D. candidate in machine learning / deep learning for medical imaging purposes. This project aims to further develop RescueDoppler - a new and proprietary solution for improved outcomes after a sudden cardiac arrest that measures blood flow continuously and non-invasively in the carotid artery, developed by CIMON medical.
The main goal of this Ph.D. is to extend the RescueDoppler technology with AI-based tools that can give real-time assistance regarding the quality of the chest compressions in the case of a sudden cardiac arrest and detect automatically successful restoration of blood flow. The RescueDoppler system includes a small and lightweight ultrasound probe with a patch for attaching the probe to the neck, an ultrasound scanner, and proprietary software for signal analysis. The technology is operator-independent and does not require ultrasound expertise. However, interpreting the Doppler curves in a stressful situation in the field can be tedious and require experience that is not always available. With the AI tools, the operator will be presented with an easy-to-understand plot that shows the quality of the compressions and is alerted when the return of spontaneous circulation (ROSC) is detected. The AI algorithm relies on the Doppler spectrum image; even though the AI works on the Doppler spectrum, this is not presented to the operator.
A strong link to the Department of Circulation and Medical Imaging, NTNU, located at St. Olav´s Hospital, and CIMON medical is already established. Clinical Ph.D. students working on the same topic will be available during the timeframe of this project.
Your immediate leader is the group leader of computing.
Duties of the position
The project’s primary objective is to develop novel AI tools for automatic monitoring and evaluate the feasibility and clinical usefulness when combined with the RescueDoppler device. The primary input source will be Doppler spectrum images from the RescueDoppler device. Main research questions are the feasibility of the AI tools and if AI can detect the return of spontaneous circulation automatically.
Required selection criteria
- You must have a professionally relevant background in and experience with machine learning and/or modern computer vision.
- Your education must correspond to a five-year Norwegian degree program, where 120 credits are obtained at master's level.
- A master’s degree in computer science or equivalent with strong analytical skills.
- You must have a strong academic background from your previous studies and an average grade from the master's degree program, or equivalent education, which is equal to B or better compared with NTNU's grading scale. If you do not have letter grades from previous studies, you must have an equally good academic basis. If you have a weaker grade background, you may be assessed if you can document that you are particularly suitable for a PhD education.
- Master's students can apply, but the master's degree must be obtained and documented by before the start date.
- You must meet the requirements for admission to the faculty's doctoral program.
- Excellent programming skills (Python/C++) and good knowledge of key programming languages and frameworks used in machine learning.
- Excellent written and oral English.
The appointment is to be made in accordance with Regulations on terms of employment for positions such as postdoctoral fellow, Phd candidate, research assistant and specialist candidate and Regulations concerning the degrees of Philosophiae Doctor (PhD) and Philosodophiae Doctor (PhD) in artistic research national guidelines for appointment as PhD, post doctor and research assistant
Preferred selection criteria
• Medical imaging related knowledge (e.g. ultrasound, Doppler imaging).
• Interested in the innovation processes related to the medical domain.
- Ability to work independently as well as in cross-disciplinary teams.
- Ability to interact and collaborate with actors in academia, public sector and industry.
- Ability to thrive and contribute to the work environment.
- Be self-motivated, focused, and goal-oriented, be committed and keep deadlines, be flexible, reliable, and solution-orientated, be innovation-driven, enthusiastic, and ambitious.
- Be scientifically curious and open to new research challenges, demonstrate persistence in addressing technical problems.
- Good communication and dissemination skills.
Emphasis will be placed on personal and interpersonal qualities.
- exciting and stimulating tasks in a strong international academic environment
- an open and inclusive work environment with dedicated colleagues
- favourable terms in the Norwegian Public Service Pension Fund
- employee benefits
Salary and conditions
As a PhD candidate (code 1017) you are normally paid from gross NOK 501 200 per annum before tax, depending on qualifications and seniority. From the salary, 2% is deducted as a contribution to the Norwegian Public Service Pension Fund.
The period of employment is 3 years (without 25 % teaching duties).
Appointment to a PhD position requires that you are admitted to the PhD programme in PhD programme in Computer Science within three months of employment and that you participate in an organized PhD programme during the employment period.
The engagement is to be made in accordance with the regulations in force concerning State Employees and Civil Servants, and the acts relating to Control of the Export of Strategic Goods, Services and Technology. Candidates who by assessment of the application and attachment are seen to conflict with the criteria in the latter law will be prohibited from recruitment to NTNU.
After the appointment you must assume that there may be changes in the area of work.
It is a prerequisite you can be present at and accessible to the institution daily.
About the application
The application and supporting documentation to be used as the basis for the assessment must be in English.
Publications and other scientific work must follow the application. Please note that your application will be considered based solely on information submitted by the application deadline. You must therefore ensure that your application clearly demonstrates how your skills and experience fulfil the criteria specified above.
The application must include:
- CV and certificates.
- Transcripts and diplomas for bachelor's and master's degrees. If you have not completed the master's degree, you must submit a confirmation that the master's thesis has been submitted.
- A copy of the master's thesis. If you recently have submitted your master's thesis, you can attach a draft of the thesis. Documentation of a completed master's degree must be presented before taking up the position.
- Project proposal.
- Name and contact information of three referees.
- If you have publications or other relevant research work.
If all, or parts, of your education has been taken abroad, we also ask you to attach documentation of the scope and quality of your entire education, both bachelor's and master's education, in addition to other higher education. Description of the documentation required can be found here. If you already have a statement from NOKUT, please attach this as well.
We will take joint work into account. If it is difficult to identify your efforts in the joint work, you must enclose a short description of your participation.
In the evaluation of which candidate is best qualified, emphasis will be placed on education, experience and personal and interpersonal qualities. Motivation, ambitions, and potential will also count in the assessment of the candidates.
NTNU is committed to following evaluation criteria for research quality according to The San Francisco Declaration on Research Assessment - DORA.
NTNU believes that inclusion and diversity is our strength. We want to recruit people with different competencies, educational backgrounds, life experiences and perspectives to contribute to solving our social responsibilities within education and research. We will facilitate for our employees’ needs.
NTNU is working actively to increase the number of women employed in scientific positions and has a number of resources to promote equality.
The city of Trondheim is a modern European city with a rich cultural scene. Trondheim is the innovation capital of Norway with a population of 200,000. The Norwegian welfare state, including healthcare, schools, kindergartens and overall equality, is probably the best of its kind in the world. Professional subsidized day-care for children is easily available. Furthermore, Trondheim offers great opportunities for education (including international schools) and possibilities to enjoy nature, culture and family life and has low crime rates and clean air quality.
As an employee at NTNU, you must at all times adhere to the changes that the development in the subject entails and the organizational changes that are adopted.
A public list of applicants with name, age, job title and municipality of residence is prepared after the application deadline. If you want to reserve yourself from entry on the public applicant list, this must be justified. Assessment will be made in accordance with current legislation. You will be notified if the reservation is not accepted.
If you have any questions about the position, please contact Gabriel Hanssen Kiss, telephone +47 91 89 79 45, email email@example.com. If you have any questions about the recruitment process, please contact HR, e-mail: HR@idi.ntnu.no.
If you think this looks interesting and in line with your qualifications, please submit your application electronically via jobbnorge.no with your CV, diplomas and certificates attached. Applications submitted elsewhere will not be considered. Upon request, you must be able to obtain certified copies of your documentation.
Application deadline: 15.04.23
NTNU - knowledge for a better world
NTNU - knowledge for a better world
The Norwegian University of Science and Technology (NTNU) creates knowledge for a better world and solutions that can change everyday life.
Department of Computer Science
We are the leading academic IT environment in Norway, and offer a wide range of theoretical and applied IT programmes of study at all levels. Our subject areas include hardware, algorithms, visual computing, AI, databases, software engineering, information systems, learning technology, HCI, CSCW, IT operations and applied data processing. The Department has groups in both Trondheim and Gjøvik. The Department of Computer Science is one of seven departments in the Faculty of Information Technology and Electrical Engineering .