PhD Research Fellow in Machine Learning for Sleep-Related Respiratory Disorders

7th December 2022
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English

• English

English
PhD Research Fellow in Machine Learning for Sleep-Related Respiratory Disorders
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About the position

Position as PhD Research Fellow in explainable machine learning (ML) for sleep-related disorders available at the Department of Informatics, University of Oslo.

No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo. Preferred starting date as soon as possible.

The PhD research fellowship is a full-time position with a fixed-term period of three years. Candidates who can and want to contribute to teaching and supervision at the department may be offered an additional year of teaching-related compulsory duties in the early stages of the contract period. In this case, the appointment period will be extended to a total of four years, where compulsory duties will be spread out over the full contract period, averaging 25% per year.

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Job description

The position is part of the RESPIRE project funded by the Research Council of Norway (https://www.mn.uio.no/ifi/english/research/projects/respire/index.html ). Respire is an interdisciplinary research project with partners in medicine (Institute of Clinical Medicine (UiO), Oslo University Hospital, Lovisenberg Diakonale Sykehus), ethics (Centre for Medical Ethics (UiO), law (Department of Private Law (UiO), and computer science (Department of Informatics (UiO), Department of Computer Science (National University of Singapore). The goal of RESPIRE is to develop machine learning (ML) solutions for sleep-related disorders that are (1) explainable to the different users, including patients, health professionals, and ML developers, and (2) responsible with respect ethical and legal considerations.

The main tasks of this position are as follows:

• Investigate recent consumer electronics for their use to monitor the sleep of young patients including infants
• Develop ML solutions to analyze the sleep monitoring data from these devices
• Support the data acquisition process, i.e., sleep monitoring of patients
• Contribute to the development of an explainability framework for the ML solutions in collaboration with project members of all involved scientific disciplines
• Contribute to the development of a data warehouse solution for the data collected and analyzed in the project
• Apply the explainability framework to evaluate the ML solutions

Qualification requirements

The Faculty of Mathematics and Natural Sciences has a strategic ambition to be among Europe’s leading communities for research, education and innovation. Candidates for these fellowships will be selected in accordance with this, and expected to be in the upper segment of their class with respect to academic credentials.

• Master’s degree or equivalent in Informatics/Computer Science
• Foreign completed degree (M.Sc.-level) corresponding to a minimum of four years in the Norwegian educational system

The successful candidate must document practical experience and knowledge with at least two of the following challenges:

• ML for time-series data
• Application of ML in the medical domain
• Interpretable ML or explainable AI
• Advanced data management solutions (data warehouse solutions)

The successful candidate should be interested in interdisciplinary collaboration and to understand scientific methods used in medics, ethics, and law.

Candidates speaking a Scandinavian language will be preferred due to interaction with medical personnel and patients at the Oslo University Hospital.

Interest and experience in teaching responsibilities will be an advantage.

Applicants who are in the process of completing their PhD degree must submit their PhD thesis by the application deadline.

Grade requirements. The norm is as follows:

• the average grade point for courses included in the Bachelor’s degree must be C or better in the Norwegian educational system
• the average grade point for courses included in the Master’s degree must be B or better in the Norwegian educational system
• the Master’s thesis must have the grade B or better in the Norwegian educational system
• Fluent oral and written communication skills in English
• English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements: http://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8

The purpose of the fellowship is research training leading to the successful completion of a PhD degree.
The fellowship requires admission to the PhD programme at the Faculty of Mathematics and Natural Sciences. The application to the PhD programme must be submitted to the department no later than two months after taking up the position. For more information see:

•  http://www.uio.no/english/research/phd/
•  http://www.mn.uio.no/english/research/phd/

Personal skills

Good communication skills are important, both for the interdisciplinary work as well as potential interactions with patients.

We offer

• Salary NOK 501 200– 544 400 per year depending on qualifications and seniority as PhD Research Fellow (position code 1017)
• Attractive welfare benefits and a generous pension agreement
• A highly dynamic and motivated team of international researchers
• Career development programmes , professional courses and workshops
• Oslo’s family-friendly surroundings with their rich opportunities for culture and outdoor activities

How to apply

The application must include:

• Cover letter - statement of motivation and research interests
• CV (summarizing education, positions and academic work - scientific publications)
• Copies of the original Bachelor and Master’s degree diploma, transcripts of records and
• Two letters of recommendation
• Documentation of English proficiency
• List of publications and academic work that the applicant wishes to be considered by the evaluation committee
• Names and contact details of 2-3 references (name, relation to candidate, e-mail and telephone number)

The application with attachments must be delivered in our electronic recruiting system, please follow the link “apply for this job”. Foreign applicants are advised to attach an explanation of their University's grading system. Please note that all documents should be in English (or a Scandinavian language).

Applicants will be called in for an interview.

Formal regulations

Please see the guidelines and regulations for appointments to Research Fellowships at the University of Oslo.

No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo.

According to the Norwegian Freedom of Information Act (Offentleglova) information about the applicant may be included in the public applicant list, also in cases where the applicant has requested non-disclosure.

The University of Oslo has an agreement for all employees, aiming to secure rights to research results etc.

The University of Oslo aims to achieve a balanced gender composition in the workforce and to recruit people with ethnic minority backgrounds.

Contact information

For further information please contact: Professor Thomas Plagemann, phone: +47 228 52743, e-mail: [email protected] or Professor Vera Goebel, phone: +47 228 52402, e-mail:  [email protected]

For questions regarding the recruitment system, please contact HR Adviser Therese Ringvold, e-mail: [email protected]

About the University of Oslo 

The University of Oslo is Norway’s oldest and highest rated institution of research and education with 28 000 students and 7500 employees. Its broad range of academic disciplines and internationally esteemed research communities make UiO an important contributor to society. 

The Department of Informatics (IFI) is one of nine departments belonging to the Faculty of Mathematics and Natural Sciences. IFI is Norway’s largest university department for general education and research in Computer Science and related topics. 

The Department has more than 1800 students on bachelor level, 600 master students, and over 240 PhDs and postdocs. The overall staff of the Department is close to 370 employees, about 280 of these in full time positions. The full time tenured academic staff is 75, mostly Full/Associate Professors..

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Deadline

7th December 2022

Employer

University of Oslo

Municipality

Oslo

Scope

Fulltime (1 stillinger) Fulltime (%)

Duration

Engagement

Place of service

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