PhD Candidate in the neural Networks for Automatic bone fracture detection (GAP MSCA - DC7)

7 Feb 2024
Job Information

Organisation/Company

NORWEGIAN UNIVERSITY OF SCIENCE & TECHNOLOGY - NTNU

Research Field

Computer science
Engineering
Medical sciences

Researcher Profile

Recognised Researcher (R2)
First Stage Researcher (R1)
Established Researcher (R3)

Country

Norway

Application Deadline

13 Feb 2024 - 00:00 (UTC)

Type of Contract

Temporary

Job Status

Full-time

Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme

Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

About the job

For a position as a PhD Candidate, the goal is a completed doctoral education up to an obtained doctoral degree.

We are looking for a PhD candidate for one of 11 PhD positions in Marie Sklodowska-Curie Action (MSCA) GAP project. The main objective of GAP MSCA Doctoral Network project envisions novel pathways for addressing the fragility fracture crisis from a multi-scale perspective, including patient-specific preventive and advanced treatment solutions.

The vision of GAP MSCA project is to educate young and talented scientists towards a combined high-level experimental and numerical approach for the early-stage accurate, precise detection and mini-invasive treatment of bone fractures, shedding some light on bone micro-scale alterations due to pathologies.

GAP network gathers excellent academic centers that have decennial experience in the field of bone multi-perspective analysis, documented by scientific papers published in high impact-factor journals, and by previous EU funded research projects. These institutions offer transversal competencies in multiple fields, such as mechanics (POLIMI, TCD), biomedical engineering (TUE, TUD), computer science (IMPAN, NTNU), biological and biochemical science (EMPA, CNRS). GAP network puzzle is completed by three other essential partners: renowned research center, i.e. ELETTRA synchrotron, unique for unprecedent high-resolution images of bones, clinical (IOG) and social institutions (CATT).

For additional information about the GAP MSCA project, please visit the project website .

Description of DC7 PhD position

Topic in brief:

The aim is to implement an approach based on artificial intelligence (AI) in the form of CNN to automatically detect cracks and morphological indices in order to manage the large amount of data obtained from Synchrotron and SEM images. This automatic tool will allow the analysis of a large number of samples to statically quantify the indices characterizing healthy and pathological bones. The AI-tool permits to classify the physio-pathological conditions, as an aid in the clinical diagnosis.

Objectives:

(1) To define a quantitative framework, based on AI, for bone micro-cracks automatic description and classification; (2) to define morphological indices to classify healthy and pathological bones; (3) to compare the approach based on artificial intelligence with the topological one; (4) to validate the micro-scale morphological indices.

Expected results:

(1) A quantitative framework, based on convolutional neural networks, able to detect the micro-cracks from the images acquired at the synchrotron. The ground truth is the manual segmentation of synchrotron slices; (2) validation of the framework by the comparison with experimental measurements; (3) the definition of micro-scale indices to evaluate crack morphological characteristics; (4) validation of micro-scale morphological indices; (5) classification of the micro-morphologies and damages of healthy and pathological bones.

Planned secondments:

(1) Prof. Dlotko (IMPAN): to discuss and compare the different approaches to automatically detect cracks from images; (2) Prof. Carradò (CNRS): to measure micro-scale morphological indices and cracks from SEM 3D images

Your immediate leader is Associate Professor Chao Gao.

Duties of the position

• take part in the mandatory PhD research education programme
• develop a quantitative deep-learning-based framework to detect the micro-cracks and validate the developed framework
• define micro-scale indices to evaluate crack morphological characteristics and validate developed the indices
• classify the micro-morphologies and damages of healthy and pathological bones
• participate in other relevant research activities through our international collaborators
• conduct and publish high-level research at peer-reviewed journals and international conferences
• write and defend a PhD thesis

Required selection criteria

• you must have a professionally relevant background in one or more of the following subject areas: Materials Engineering, Mechanical Engineering, Biomedical Engineering, Computer Engineering
• your education must correspond to a five-year Norwegian degree program, where 120 credits are obtained at master's level
• 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.
• you must meet the requirements for admission to the faculty's doctoral program
• excellent written and oral English
• strong background in applying deep learning neural networks on image segmentation associated with bone fracture
• excellent programming skills in Python and Matlab

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

• experience in synchrotron-imaging techniques
• knowledge and technical skills of mechanical testing methods
• experience and knowledge of finite element analysis by using Abaqus

Personal characteristics

• strong interest and self-motivated attitude to explore scientific questions
• think and work independently
• team player with cooperative attitude
• good communication skills

Emphasis will be placed on personal and interpersonal qualities.

We offer

• 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 532 200 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.

Appointment to a PhD position requires that you are admitted to the PhD programme in [subject area] (Link to website, if applicable) within three months of employment, and that you participate in an organized PhD programme during the employment period.

After the appointment you must assume that there may be changes in the area of work.

The position is subject to external funding from Marie Sklodowska-Curie Action (MSCA) for GAP project .

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 be attached to 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
• motivation letter justifying your interest and fit for the position
• name and contact information of referees and their recommendation letters
• academic works – published or unpublished – that you would like to be considered in the assessment

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.

General information

Working at NTNU

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 Associate Professor Chao Gao, email: [email protected] . If you have any questions about the recruitment process, please contact HR Consultant Hedda Winnberg, e-mail: [email protected] .

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: 13.02.2024

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 Mechanical and Industrial Engineering

We educate graduates who can create new products, operate and maintain products, and manage projects. The Department has a variety of bachelor’s and master’s degree programmes. We conduct wide-ranging research in fields such as technology, energy, product quality and development, and productivity. The Department of Mechanical and Industrial Engineering  is one of eight departments in the Faculty of Engineering.

Deadline 13th February 2024
Employer NTNU - Norwegian University of Science and Technology
Municipality Trondheim
Scope Fulltime
Duration Temporary
Place of service Richard Birkelands vei 2B, 7034 Trondheim

Requirements
Additional Information
Work Location(s)

Number of offers available

1

Company/Institute

NORWEGIAN UNIVERSITY OF SCIENCE & TECHNOLOGY - NTNU

Country

Norway

City

Trondheim

Geofield

Where to apply

Website

https://www.timeshighereducation.com/unijobs/listing/364979/phd-candidate-in-th…

Contact

City

Trondheim

STATUS: EXPIRED