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Postdoctoral Research Fellow in Al Trustworthiness and Sustainability Assessment

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.

The Department of Computer Science has a vacancy for a Postdoctoral Research Fellow in the field of Artificial Intelligence (AI) is offered for the period from March 2023 of 2 years, with a possible extension of 1 year.

 The Postdoctoral Fellow will be affiliated to the Department of Computer Science and to the OsloMet/SimulaMet AI Lab, working within the Center of Research Excellence, NordSTAR - Nordic Center for Sustainable and Trustworthy Artificial Intelligence Research, which is hosted by OsloMet and includes partners from several research centres and universities in Norway, such as Simula Research Laboratory and the Norwegian University of Science and Technology (NTNU).

NordSTAR is one of the five Centers of Research Excellence at OsloMet. Modern AI can document impressive results and even outperform human beings on many tasks. The methods are however also associated with many challenges that limit the trust when the methods are applied. NordSTAR aims to improve trustworthiness and sustainability in AI methods by developing frameworks which enable to assess how trustworthy and sustainable AI methods, algorithms and tools are. The approach is based in four challenges. (i) It is usually hard to understand the mechanism in complex AI methods leading to the predictions; (ii) there are important human factors in the application of AI, both legally and ethically, (iii) the methods usually are not able to quantify how certain they are about their decisions, (iv)  running large and complex machine learning systems opens up security issues. NordSTAR is composed by 4 main research areas: “Understandable and explainable models”, “Human Factors in AI”, “Security, safety and reliability”, “Biologically inspired computational systems”, “Quantum AI”.

Project overview

The project for this position will be within the main goals of NordSTAR, namely developing assessment frameworks of the sustainability and trustworthiness of AI methods, algorithms and tools. The candidate’s project will intersect some of NordSTAR’s topics:

Your duties and responsibilities will be to

Qualification requirements

General criteria for appointments to academic positions are covered by the Forskrift om ansettelsesvilkår for stillinger som postdoktor, stipendiat, vitenskapelig assistent og spesialistkandidat

The following will be emphasized

It is important to OsloMet to reflect the population of our region, and all qualified candidates are welcome to apply. We make active efforts to further develop OsloMet as an inclusive workplace and to adapt the workplace if required. You are also welcomed to apply for a position with us if you have experienced periods where you have not been in work, education or training.

Application process

If you would like to apply for the position you must do so electronically through our recruitment system. You will be assessed by an Expert Committee. You must upload the following documents with the application within the application 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 either English or a Scandinavian language. Translations must be authorised. Originals must be presented if you are invited for an interview. OsloMet performs document checks in order to give you as a candidate a proper evaluation and ensure fair competition.

Before submitting the application documents to the Expert Committee, all applications will be reviewed by the faculty and applicants who do not meet the formal qualification requirements will not be submitted for assessment.

OsloMet has adhered to the principles in the DORA declaration and obliged the institution to follow the recommendations in this declaration.

We offer

Practical information about relocation to Oslo and living in Norway

The position is remunerated in accordance with the Basic Collective Agreement for the Civil Service and OsloMets salary policy, job code 1352 Postdoctoral Research Fellow. The salary is NOK 543 500-702 100 per year, salary scale 60 -74. A higher salary may be considered for particularly well qualified applicants. 

Other information

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

 

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.