Faculty of Technology, Art and Design, Department of Computer Science

Oslo Metropolitan University is Norway's third largest university with almost 22,000 students and over 2,500 employees. We have campuses in central Oslo and at Romerike. OsloMet educates students and conducts research that contributes to the sustainability of the Norwegian welfare state and the metropolitan region.

The Faculty of Technology, Art and Design (TKD) offers higher education and research and development (R&D) activities within technical subjects, arts and design. The Faculty has approximately 3.000 students and 280 staff members and is situated at Pilestredet Campus in downtown Oslo and at Kjeller Campus in Viken.

The Department of Computer Science offers three bachelor’s degree programmes, a master’s degree programme, and is part of a cross-departmental PhD program. Academic staff at the department are pursuing research in a wide range of areas including computer science, the natural sciences, and innovation and management. Both students and researchers are also involved in an increasing number of interdisciplinary initiatives across the university. 
The department of Computer Science has approximately 70 staff members and 800 students. 
There are currently several research groups at the Department.

A temporary Postdoctoral Researcher position in the field of ‘Machine Learning and Deepfake is offered for the period of 6 months in the Department of Computer Science at Oslo Metropolitan University.

The position will be part of OsloMet Artificial Intelligence Lab (AI Lab), which is a joint research centre for OsloMet – Oslo Metropolitan University and SimulaMet. It administers research and innovation projects in artificial intelligence, both applied and basic research, including theory and the use of machine learning in different areas.

The project addresses deepfake technologies with a focus on detection of deepfake videos. Deepfake technologies, which rely on deep learning, are developing at an unprecedented rate. Malicious face-manipulated videos generated by deepfake algorithms are threatening social stability and personal privacy. Current deepfake creation uses various combinations of Deep Neural Networks like CNNs, RNNs, and GANs. The detection and combating of deepfakes is getting harder because deepfake creation methods are getting sophisticated. Most research on fake video detection has used deep learning to detect artifacts and inconsistencies of the video.

Tasks and responsibilities  

We aim at building a strategic, long-term project for the exploration of research to reduce the negative impacts of deepfake videos on people. Most of the tools and techniques developed so far in order to detect fake images and videos are also based on deep learning, and thus a battle between malicious and benign uses of deep learning methods has been rising. 

We invite an applicant fond of AI and machine learning to join our team for a 6-month collaboration with possible extension with the following agenda: 

  • Identify the state of knowledge and potential for research
  • Develop a research roadmap for the above topics
  • Initial experimentation and pre-studies with deepfake technologies for producing and detecting  deepfake media
  • Develop in cooperation with OsloMET researchers a proposal for a multi-year research project to national funding authorities that will fund a multi-year position involving the candidate
  • Prepare a research publication to disseminate the results of the research 

We look for a recently graduated – or very soon to graduate - holder of a PhD in computer science, computer engineering, computer security, data science or related disciplines whose knowledge profile fits the research area.

Qualifications requirements:

  • PhD student or PhD degree in Computer Science or Engineering related subjects with experience in one or more of the following:
    • Machine learning/deep learning
    • Deep Graph Neural Networks
    • Deep reinforced learning
    • Active Learning
  • Ability to conduct independent research
  • Proficiency in oral and written English is required 

General criteria for appointments to academic positions are covered by the Regulations for appointment and promotion to academic posts.  
 
General criteria for evaluating educational competence is described by OsloMets criterias for evaluating educational competence.

When evaluating the applications, we will emphasize: 

Emphasis is also placed on the following skills, competence and experience: 

  • Good communications and cooperation skills
  • Personal skills relevant for a good working environment
  • The applicant's topical profile evaluated against the topic of the project 

It is important for OsloMet to reflect the population of our region, and all qualified candidates are welcome to apply. We make active endeavours to further develop OsloMet as an inclusive workplace and to adapt the workplace if required. If there are periods where you have not been in work, under education or in training, you are also welcome to apply.

How to apply  

Please upload the following documents together with your application before the final date for application: 

  • CV (including the name and contact information of at least three references)
  • Full list of publications
  • Copies of certificates/diplomas
  • Full texts of the five most relevant publications
  • A copy or summary of your PhD thesis
  • Other relevant documentation 


You must upload all the documents in order for your application to be processed. The documents must be in either English or a Scandinavian language. Translations must be authorized. Originals must be presented if you are invited for an interview. OsloMet checks documents in order to give you as a candidate a proper evaluation and ensure fair competition.  

If you have documents that cannot be uploaded electronically, please contact HRTKD@oslomet.no

We offer 

  • An exciting job opportunity at Norway’s third largest and most urban university
  • Participation in a dynamic professional environment and unique academic community
  • The opportunity to be part of the development of a young and ambitious university with an entrepreneurial culture
  • Academic development as part of a group of committed colleagues.
  • Opportunities for academic development in a professional research environment.

The position is remunerated in accordance with the job code 1109 Researcher, Norwegian State salary scale 60-74, NOK 535 200– 694 400 per year, or with the job code 1108 Researcher, Norwegian State salary scale 51-66, NOK 458 900 – 597 000 per year. A higher salary may be considered for particularly well-qualified applicants.

Other information

For more information about the position, feel free to contact:  

  • Professor Anis Yazidi, email:  anis.yazidi@oslomet.no
  • Professor Lothar Fritsch, email: lotharfr@oslomet.no 


If you wish to apply for the position, please do so via our application portal.

References & Background

  1. Hussain, S., Neekhara, P., Jere, M., Koushanfar, F., & McAuley, J. (2021). Adversarial deepfakes: Evaluating vulnerability of deepfake detectors to adversarial examples. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (pp. 3348-3357).
  2. Zi, B., Chang, M., Chen, J., Ma, X., & Jiang, Y. G. (2020, October). WildDeepfake: A Challenging Real-World Dataset for Deepfake Detection. In Proceedings of the 28th ACM International Conference on Multimedia (pp. 2382-2390).
  3. Yu, P., Xia, Z., Fei, J., & Lu, Y. (2021). A Survey on Deepfake Video Detection. IET Biometrics.
  4. Eirik Molde Bårli, Anis Yazidi, Enrique Herrera Viedma ,Hårek  Haugerud DoS and DDoS Mitigation Using Variational Autoencoders Submitted to Computer Networks, Under Revision in Computer Networks, https://arxiv.org/abs/2105.06899  
Type of employment Temporary position (shorter than 10 days)
Contract type Full time
First day of employment Upon agreement
Salary NOK 458 900 - 694 400
Number of positions 1
Full-time equivalent 100%
City Oslo
County Oslo
Country Norway
Reference number 21/05451
Contact
  • Anis Yazidi, 46744088
Published 02.Jun.2021
Last application date 15.Jun.2021 11:59 PM CEST

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