PhD Research Fellow in Brain Controlled Networked Interactions
About the position
Position as PhD Research Fellow in the brain controlled networked interactions available at Networks and Distributed Systems, Department of Informatics, University of Oslo.
No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo. Starting date no later than October 1, 2024.
The fellowship period is three (3) years.
A fourth year may be considered with a workload of 25 % that may consist of teaching, supervision duties, and/or research assistance. This is dependent upon the qualification of the applicant and the current needs of the department.
Knowledge development in a changing world – Science and technology towards 2030.
The Faculty of Mathematics and Natural Sciences
Job description
The Sustainable Immersive Networking Lab (SINLAB) is seeking a new member for its multi-disciplinary team that holistically explores networked interactions. SINLAB explores human-centric, inclusive processes, where the challenges of networked interaction are tackled by understanding human action and perception. In essence, we want to enable people to truly experience networked interactions with all their senses (e.g. audio, visual and haptic), eventually leading to natural social interaction across distances.
SINLAB conducts systems research to augment the capabilities of users by enabling them to act in remote physical spaces in a natural manner and to experience the effects of remote actions. The research is conducted for application areas, including health, industry, education, sports, entertainment, and creative applications. The team explores resource management in networks and distributed systems, handling audiovisual and haptic modalities from capture to playout, context-specific action prediction, real-time interaction among humans and between humans and a remote environment, and quality of experience.
The selected applicant will contribute to SINLAB’s ongoing research by focusing on brain controlled networked interactions. The main challenge with networked interactions is that haptic feedback has very stringent delay requirements as low as 20 milliseconds. Therefore, performing such actions remotely with both action and reaction traversing long distances is far beyond our technical capabilities today. Even the developments in 5G and beyond networks that specifically target significant latency reductions are not sufficient due to physical as well as resource limitations.
To overcome the latency challenge, we need to design latency hiding functions that can accurately forecast the activity to hide the latency by compensating for the difference between the latency limits and perceptual tolerance, so that the networked interaction can be provided with a high degree of realism. The accuracy of such forecasts is essential, and we will therefore leverage the Brain Machine Interfaces (BMIs) to exploit brain signals via non-invasive electroencephalogram (EEG). These signals will provide the person’s future movement onset and their cognitive state during the interaction, hence enabling accurate predictive machine learning models to forecast and orchestrate the interaction elements and adjust allocation of network and computing resources to reduce excessive network latencies.
The applicant’s central research question will be how can we design latency hiding functions that can accurately forecast the activity using BMIs to compensate for the difference between the latency limits and perceptual tolerance, so that the networked interaction can be provided with a high degree of realism? Addressing this research question will be part of the team’s ambition to provide immersive networked interactions. The applicant will be collaborating highly with the other members of the team. Furthermore, the applicant will have the opportunity to collaborate with academic and industrial researchers in Europe through ongoing national and international projects, and through our association with centers of excellence in Norway and abroad.
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.
Required qualifications:
- Master’s degree or equivalent in informatics, computer science/engineering, electrical/electronic engineering, cybernetics or a closely related field. A foreign completed degree (M.Sc.-level) must correspond to a minimum of four years in the Norwegian educational system.
- Documented experience in the area of networked interaction or computer-mediated interaction.
- Document knowledge about the system performance evaluation of computer systems and networks for interactive applications, preferably with BMIs, AR/VR/XR, multimodal or multimedia systems. Directly relevant areas are preferable.
- Documented programming experience
- Fluent oral and written communication skills in English
Desired qualifications:
- It is an advantage if the applicant has developed working systems, prototypes, or emulators.
- It is an advantage if the applicant has developed software in fields such as BMI, AR/VR/XR, robotics, haptics, multimedia systems or computer games requiring hand-eye-coordination.
- It is an advantage if the applicant has experience in 5G and beyond networks, or relevant technologies such as edge computing.
- It is an advantage to have experience in machine learning, in particular concerning the learning of action prediction models.
Candidates without a master’s degree have until 30 June, 2024 to complete the final exam.
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 educa-tional system
- English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements:
https://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
- The applicant must be comfortable and capable working in an open, interactive, collaborative work environment.
- The applicant must demonstrate the social responsibility and ethical awareness required to design, organize, and conduct user studies.
We offer
- Salary NOK 532 200 – 575 400 per year depending on qualifications and seniority as PhD Research Fellow (position code 1017)
- Attractive welfare benefits and a generous pension agreement
- Vibrant international academic environment
- Career development programmes
- 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 and transcripts of records
- Documentation of English proficiency if applicable
- 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.
Interviews with the best qualified candidates will be arranged.
Formal regulations
Please see the guidelines and regulations for appointments to Research Fellowships at the University of Oslo.
According to the Norwegian Freedom and 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.
UiO has an agreement for all employees, aiming to secure rights to research results a.o.
Inclusion and diversity are a strength. The University of Oslo has a personnel policy objective of achieving a balanced gender composition. Furthermore, we want employees with diverse professional expertise, life experience and perspectives.
If there are qualified applicants with disabilities, employment gaps or immigrant background, we will invite at least one applicant from each of these categories to an interview.
Contact information
For further information please contact Professor Özgü Alay, phone: +47 98485362, e-mail: ozgua@ifi.uio.no
For questions regarding Jobbnorge, please contact HR Adviser Therese Ringvold, e-mail: therese.ringvold@mn.uio.no
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 7000 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.
Deadline: 2024-02-29 at 23:59
Unit: Engineering/it
Read the job description at the university homepage or apply.