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PhD Fellowship position in Deep Generative Models of Eye-Tracking data

OsloMet – Oslo Metropolitan University is Norway’s third largest university, with nearly 22,000 students and 2,200 employees. Through the students we educate and the research we produce, the university has a direct impact on society, both in Norway and beyond. The university has two campuses, one in central Oslo and another a short distance from the city in the municipality of Lillestrøm. OsloMet is home to some of Norway’s largest and oldest educational programmes, including degree programmes in nursing, engineering and teacher education. The university is also a hub of research and technological innovation aimed at strengthening and sustaining the Norwegian welfare state.

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 4.000 students and 400 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.

PhD Fellowship position in Deep Generative Models of Eye-Tracking data

The Department of Computer Science has a vacant PhD Fellowship position in Deep Generative Models of Eye-Tracking data. PhD fellowship is connected to the Artificial Intelligence Lab (AI Lab) research group and Nordic Centre for Sustainable and Trustworthy Artificial Intelligence Research (NordSTAR).

Area of research

The position will focus on some of the main tasks of the Virtual-Eye project, namely in generative adversarial networks and stochastic modeling of eye-gaze trajectories.

About the project: As a door to the outside world and by virtue of millions of years of biological evolution, the eyes exhibit a complex scanpath behavior that is highly efficient at finding objects of interest. Novel search algorithms inspired by eye-gaze trajectories admit a list of potential applications in autonomous robotic search where the search time is critical, such as target detection in surveillance applications and visual scan for self-driving cars. Furthermore, the study of gaze has many important applications to medicine and psychology. It is observed that there is a gaze signature unique to each person which also provides information about personality traits, IQ and skills in a particular field, as well as diagnosing attention deficit hyperactivity disorder, Alzheimer’s and autism. Mathematical research tends to forego that the eyes are intrinsically linked with the cognitive process. Here, eye movements are often treated as a simple way to forage for visual information. That is, however, a crude simplification: human scan-paths reflect more than just a strategy to forage for visual information and they seem to be better than other searching strategies such as Lévy flights which operate with simplistic assumptions. Both these mathematical processes are seemingly universal in explaining the foraging behavior in processes as diverse as the hunting movement of albatrosses and sharks, the movement of swimming bacteria or the exploration of the Walt Disney Resort by children. Yet, paradoxically, the debate is still ongoing what its general form actually is. Our hypothesis in the "Virtual-Eye" project is that some of the added complexity of gaze trajectories, when compared to Lévy flights or intermittent processes, are designed to optimize the search for visual information.

PhD fellow will carry out research and experiments with human participants within the frames of the project in close collaboration with the supervisors and other staff members at the department. The research will intersect AI methods, with focus on generative adversarial networks and other machine learning methods, statistical learning and theoretical aspects of statistics and probability theory, and eye-tracking. In addition to the research tasks, the fellow will disseminate the projects results and outcomes through appropriate channels, help in administrative requirements as project partner, and help in the supervision of master projects related to the Virtual-Eye project.

The position is advertised as a 3-year position with 100% research, or a 4-year position with 75% research and 25% other tasks (teaching, supervision and/or administrative work). The goal must be to complete the PhD program/degree within the decided time frame. The decision on a 3- or 4-year position will be discussed as part of the interviews in the hiring process. The start date of the position is 01.10.2023 at the latest.

Qualification requirements and conditions

The following grade requirements are a condition for employment in the position:

Admission to the doctoral program in Engineering Science at the Faculty of Technology, Art and Design within three months of employment is a prerequisite for the position. If you already have a doctorate in a related field, you will not qualify for the position.

In assessing the applicants, emphasis will be placed on the department's overall needs and the applicant's potential for research within the field.

General criteria for employment in academic positions are covered by the Regulations on employment conditions for positions such as postdoctoral fellow, scientific assistant and specialist candidate.

Preferred selection criteria

It is important to 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 make adaptations to the workplace where required. You are also welcome to apply for a position with us if you have had periods where you have not been in employment, education or training.

We can offer you

Practical information about relocation to Oslo and living in Norway.

The position is paid according to the pay scale for Norwegian state employees, position code 1017 PhD fellow, NOK 501 200 per year.


To be considered for the position, you must upload the following documents by the application deadline:

The following language tests are approved documentation: TOEFL, IELTS, Cambridge Certificate in Advanced English (CAE) or Cambridge Certificate of Proficiency in English (CPE). In these tests, you must have achieved at least the following scores:

Official diploma and transcript must be submitted before taking up the position, no later than 01.10.2023. If your educational institution is not able to deliver an official diploma by the deadline, you must submit documentation from the institution that confirms that your master´s degree is completed by the same deadline.

We only process applications sent via our electronic recruitment system and all documents must be uploaded for your application to be processed. The documents must be in English or a Scandinavian language. Translations must be authorized. You must present originals at any interview. OsloMet checks documents, so that you as a candidate will get a real evaluation and fair competition.

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 OsloMet.

Other information

If you would like more information about the position, feel free to contact:

If you have administrative questions about the position, please contact

If you would like to apply for the position, you must do so electronically through our recruitment system.


Deadline for applications: 01.06.2023

Ref.: 23/02251


OsloMet is a Charter & Code certified institution by the EU Commisson holding the right to use the logo HR Excellence in Research (HRS4R). OsloMet is a member of the EURAXESS network supporting a positive work environment for researchers in motion. OsloMet has signed The Declaration on Research Assessment (DORA). DORA recognizes the need to improve the ways in which the outputs of scholarly research are evaluated.