Job description

Position as Researcher in Intelligent and Autonomous Edge Computing available at the Networks and Distributed systems (ND) group, Department of Informatics, University of Oslo.

The position is within a project, funded by the Research Council of Norway, called AirQMan: Towards Cognitive and Autonomous Smart City Services: The Case of Low-Latency Air Quality Management. For further information about the project, please follow this link.  The position is for a period of 1.5 years and devoted to carrying out research in the context of the AirQMan project.

 The research is conducted in collaboration with three national partners, one research institute and two state agencies:

• Norwegian Institute for Air Research
• Municipality of Oslo: Agency for Urban Environment
• Municipality of Halden: Innovation and Smart City Section

Starting date preferably no later than 01.03.2024.

More about the position

Air quality (AQ) monitoring and management (AQMS) methods have been improved significantly both in Norwegian and European cities, but further progress is needed due to some quality-driven requirements, such as low-latency AQ prediction. This can only be achieved by intelligent data processing at multiple levels of granularity. To this end, effective and intelligent tools are needed that utilize the current advances in digitization of all spheres of society, providing radical innovation of air quality management. The AirQMan project promises autonomous computational methods and techniques to develop such solutions. It extends data processing and computational intelligence from the Cloud to multiple levels of Fog nodes towards the Edge of the network. In particular, the project has the following main objectives: 1) developing a novel data processing design model that will autonomously determine the optimal data fusion processing flow, the right data sources, and the right trained deep learning (DL) model for maximizing the accuracy of AQ prediction; 2) predicting and maintaining the optimal distributed deployment over Edge-Cloud plat-forms for an efficient computation of the DL model while satisfying accuracy and latency requirements.

We are seeking a researcher who is interested in designing, developing, and evaluating techniques and frameworks related to the above. In particular, the selected candidate is expected to conduct research on designing distributed deep learning models across the Edge-Cloud continuum considering quality of service requirements (e.g., latency), as well as on autonomous deployment and migration of data processing tasks over Edge-Cloud in a highly self-aware manner. Additionally, it is expected that the researcher actively contributes to the coordination of collaboration between all partners contributing to AirQMan, including supervision of PhD candidates. 

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.

Qualifications:

• Applicants must hold a PhD degree equivalent to a Norwegian doctoral degree in in Computer Science or in a related study, with excellent results and a clear profile in one or more of the following areas: Distributed Computing, Fog/Edge Computing, Machine Learning, and Service Computing.
• The candidate must have relevant publications in internationally recognized academic confer-ences and journals. 
• The candidate should have good analytical skills and programming knowledge in Python, C++ or Java.
• The evaluation considers many aspects of excellence, as well as the personal drive and organizational skills.
• Fluent oral and written communication skills in English. 
• Doctoral dissertation must have been submitted for evaluation by the closing date. You may apply even if you have not yet completed your degree, but expect to do so before the position starts.

We offer

• Salary NOK 575 400 - 657 300 per year depending on qualifications in position as Researcher (position code 1109)
• Attractive welfare benefits and a generous pension agreement
• Professionally stimulating working environment
• Vibrant international academic environment
• Oslo’s family-friendly surroundings with their rich opportunities for culture and outdoor activities

How to apply

The application must include:

• Application letter (max. 2 pages). Please describe your motivation for applying for this position and explain how your background, research, and experience is relevant to the project. 
• CV summarizing education, positions, research experience, and other qualifying activities.
• Copies of educational certificates, academic transcript of records and letters of recommendation
• Up to 5 academic works that the applicant wishes to have considered in the assessment process 
• A list of reference persons: 2-3 references (name, relation to candidate, e-mail and phone 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).

In assessing the applications, special emphasis will be placed on the documented, academic qualifications, as well as the candidates motivation and personal suitability. Interviews with the best qualified candidates will be arranged.

Formal regulations

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.

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 Amir Taherkordi, e-mail: amirhost@ifi.uio.no or 
• Professor Frank Eliassen, e-mail: frank@ifi.uio.no

For questions regarding Jobbnorge, please contact HR Adviser: Therese Ringvold, e-mail: therese.ringvold@mn.uio.no

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