PhD Fellowship in Image Processing and Machine Learning

University of Stavanger

Norway

Ph.D fellowship in image processing and machine learning

Job description

The University of Stavanger invites applicants for a Ph.D fellowship in the field of image processing and machine learning at the Faculty of
Science and Technology, Department of Electrical Engineering and Computer Science. The position is vacant from 01.08.2021
This is a trainee position that will give promising researchers an opportunity for academic development leading to a doctoral degree.

The appointment is for three years with research duties exclusively.
The PhD student will be affiliated with the projec “NewbornTime - Improved newborn care based on video and artificial intelligence”.
The position is funded by the Norwegian Research Council

About the NewbornTime project

The NewbornTime project is about improved newborn care by using artificial intelligence (AI) for activity and event recognition in video from the
time during and after birth.
Deprivation of oxygen to an infant during and after birth might lead to birth asphyxia, one of the leading causes of newborn deaths, cerebral
palsy and other long-term damage. According to guidelines, a newborn in need of help to start breathing should be resuscitated immediately
after birth. Resuscitation activities include stimulating, clearing airways, and perform bag-mask-ventilation. In Norway, approximately 10% of
term infants need stimulation and around 3% need bag-mask ventilation.
NewbornTime will produce a timeline describing events and activities performed on a newborn. Accurate time of birth will be detected using AI
models from thermal videos collected in the delivery room. Activity recognition will be performed using AI in the form of deep convolutional
neural networks (CNN) on thermal and RGB video from the resuscitation. The system will be designed to recognize multiple time-overlapping
activities. Care will be given to make the AI models robust, reliable, general, and adaptive to be able to use it at different hospitals and settings.

The timelines will be used to evaluate compliance to guidelines and identify successful resuscitation activity patterns. It can further be useful in
a de-briefing and quality improvement tool.
The project is a collaboration between University of Stavanger (UiS), Stavanger University Hospital (SUS), Laerdal Medical and BitYoga. UiS,
SUS and Laerdal has long experience in collaborative research on newborn care. They have documented promising results on detecting
activities using resuscitation videos from a hospital in Tanzania. In NewbornTime the data collection will be performed at SUS. BitYoga and
Laerdal will ensure smart GDPR compliant data-contracts and data-platforms. UiS will develop site-adaptive AI methods for activity recognition
in video.

This PhD project will be in the topic of event and activity recognition from videos. The candidate will work on developing deep neural network
architectures and semi-supervised learning of events and activities from untrimmed videos. The aim is to detect time of birth automatically and
recognize important resuscitation events and activities.

Qualification requirements

We are looking for applicants with a strong academic background who have completed a five-year master degree (3+2) within electrical
engineering, computer science or machine learning, preferably acquired recently; or possess corresponding qualifications that could provide a
basis for successfully completing a doctorate.

To be eligible for admission to the doctoral programmes at the University of Stavanger both the grade for your master’s thesis and the weighted
average grade of your master’s degree must individually be equivalent to or better than a B grade. If you finish your education (masters
degree) in the spring of 2021 you are also welcome to apply.

Applicants with an education from an institution with a different grade scale than A-F should attach a confirmed conversion scale that shows
how the grades can be compared with the Norwegian A-F scale. You can use these conversion scales to calculate your points for admission.
The applicant is further required to have subjects like:
signal- and/or image processing
machine learning
programming

Furthermore, it is an advantage to have knowledge in deep neural networks.
Emphasis is also placed on your:
motivation and potential for research within the field
your professional and personal skills for completing the doctoral degree within the timeframe
ability to work independently and in a team, be innovative and creative
ability to work structured and handle a heavy workload
ability to work structured and handle a heavy workload
having a good command of both oral and written English
Requirements for competence in English

A good proficiency in English is required for anyone attending the Ph.D program. International applicants must document this by taking one of
the following tests with the following results:
TOEFL - Test of English as a Foreign Language, Internet-Based Test (IBT). Minimum result: 90
IELTS - International English Language Testing Service. Minimum result: 6.5
Certificate in Advanced English (CAE) og Certificate of Proficiency in English (CPE) from the University of Cambridge
PTE Academic - Pearson Test of English Academic. Minimum result: 62

The following applicants are exempt from the above requirements:

Applicants with one year of completed university studies in Australia, Canada, Ireland, New Zealand, United Kingdom, USA
Applicants with an International Baccalaureate (IB) diploma
Applicants with a completed bachelor's and / or master's degrees taught in English in a EU/EEA country

We offer

varied duties in a large, exciting and socially important organisation
an ambitious work community which is developing rapidly. We strive to include employees at all levels in strategic decisions and promote an informal atmosphere with a flat organisational structure.
salary in accordance with the State Salary Scale, l.pl 17.515, code 1017, NOK 482 200 gross per year with salary
development according to seniority in the position. From the salary, 2% is deducted as a contribution to the Norwegian Public Service Pension Fund.
automatic membership in the Norwegian Public Service Pension Fund, which provides favourable insurance- and retirement benefits
favourable membership terms at a gym and at the SIS sports club at campus
employment with an Inclusive Workplace organisation which is committed to reducing sick leave, increasing the proportion of
employees with reduced working capacity, and increasing the number of professionally active seniors
"Hjem-jobb-hjem" discounted public transport to and from work
as an employee in Norway, you will have access to an optimal health service, as well as good pensions, generous maternity/paternity
leave, and a competitive salary. Nursery places are guaranteed and reasonably priced
relocation programme
language courses: On this page you can see which language courses you may be entitled to (look up “language courses” under
employment conditions)

Diversity

Being independent, involving and innovative are the university’s values. We consider diversity to be a resource in our working and learning
environment, and we are keen to show respect for one another’s differences and backgrounds. Universal design must characterise of physical
and digital learning environment, and the workplace will, if necessary, be facilitated for employees with disabilities.


If you find the position to be interesting, we encourage you to apply, regardless of gender, disability, cultural background or any periods of
unemployment.
The university aims to recruit more women into positions as Ph.d Fellowship in the subject area; thus, if several applicants are considered to
have equal qualifications, a femal applicant will be given priority over a male.

Contact information

More information on the position can be obtained from Professor Kjersti Engan, e-mail: kjersti.engan@uis.no or Associate Professor Øyvind
Meinich-Bache, e-mail: oyvind.meinich-bache@uis.no.
Information about the appointment procedure can be obtained from HR-consultant, e-mail: rekruttering@uis.no.
Application
To apply for this position please follow the link "Apply for this job". Your application letter, relevant education and work experience as well as
language skills must be registered here. In your application letter, you must state your research interests and motivation for the position.
The following documents must be uploaded as attachments to your application:
CV with a full summary of your education and experience
publications or other relevant research work
references, certificates/diplomas and other documentation that you consider relevant
Please note that applications are only evaluated based on the information available in Jobbnorge at the application deadline. You should
ensure that your application shows clearly how your skills and experience meet the criteria which are set out above.

The documentation must be available in either a Scandinavian language or in English. If the total size of the attachments exceeds 30 MB, they
must be compressed before upload.
Please note that information on applicants may be published even if the applicant has requested not to be included in the official list of
applicants - see Section 25 of the Freedom of Information Act.

UiS only considers applications and attachments registered in Jobbnorge.
General information
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 UiS.
Employment as Ph.D Fellow is regulated in "Regulations concerning terms and conditions of employment for the posts of post-doctoral
research fellow and research fellow, research assistant and resident".

Your qualifications for the position, based on documentation registered in Jobbnorge, will be assessed by an internal expert committee. Based
on the committee's statement, relevant applicants will be invited to an interview before any recommendations are made. References will also be
obtained for relevant candidates. More about the hiring process on our website.
The appointee will be based at the University of Stavanger, with the exception of a stay abroad at a relevant centre of research.
It is a prerequisite that you have a residence which enables you to be present at/available to the academic community during ordinary working
hours.


The position has been announced in both Norwegian and English. In the case of differences of meaning between the texts, the Norwegian text
takes precedence.
UiS - challenge the well-known and explore the unknown
Jobbnorge ID: 200178, Deadline: Monday, March 15, 2021


In your application, please refer to Polytechnicpositions.com

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