PhD fellowship in Applied Information Technology - Studying the trustworthiness in the context of AI
Deadline: 15.05.2025
Publisert
Kristiania University of Applied Sciences offers study programs in management, organization, marketing, communication, computer science, information technology, health sciences, innovation and creative arts. Kristiania University of Applied Sciences is Norway's largest independent comprehensive university college with its 24,000 students and a large education offering in Oslo, Bergen and online. Our mission is to strongly contribute to the country's social and economic development through problem-driven and applied knowledge development and dissemination, in close cooperation with society at large.
Intro school
The School of Economics, Innovation, and Technology delivers research and study programmes at bachelor and master level. The emphasis for both research and study programmes are on economics, innovation, digitalization and information technology. Information science, information systems and the interaction between technology and human beings are other exciting focus areas.
We also have our own PhD program in Applied Information Technology.
The department is expanding its online offers and offers in further and continuing education in cooperation with working life. The department has well-established research groups and research labs at a high international level.
About position
Kristiania University of Applied Sciences is offering a fully funded Ph.D. fellowship in Applied Information Technology. The successful applicant will be included in a team of researchers with ambitious plans to further develop research and pedagogical activities related to Applied Information Technology at the university. Collaboration with other institutes is expected, namely with University of Oslo, Oslo Metropolitan University and Oslo University Hospital.
The PhD project should aim to (1) investigate methods for assessing the different aspects of trustworthiness of AI algorithms, namely performance, explainability, fairness, robustness, security and user-feedback trust, and (2) explore a possible implementation which enable to optimize the trade-offs between them. The project will focus on use-cases from the health and business sectors, and it is foreseen a strong collaboration with experts from those areas, benefiting from some ongoing projects with the supervision team of this project.
The PhD candidate will:
design and implement deep neuro network architectures with the aim of prediction and/or decision-making in applied topics, e.g., clinical diagnosis and management support;
design and implement standard tools to assess, e.g., performance, complexity, explainability and fairness of AI algorithms;
develop new tools to assess the different aspects of AI trustworthiness and combine them as a multi-objective framework able to be optimized according to prescribed requirements;
implement mechanisms to trace and justify model decisions using symbolic representations; and,
disseminate results in top-tier AI conferences and journals and collaborate with industry/business/academic partners.
The candidates must have:
Master’s degree (120 ECTS or equivalent) in computer science, AI, data science, or a related field with a grade B or better on the master’s thesis and for the master’s degree in total. The master’s thesis must be a minimum of 30 ECTS or equivalent.
Relevant 180 ECTS bachelor’s degree.
Solid technical background in machine learning, deep learning (e.g., transformer architectures, multimodal models).
Strong proficiency in programming, such as Python and deep learning libraries (PyTorch/TensorFlow).
Good mathematical background (e.g., linear algebra, discrete mathematics).
Some familiarity with methods of AI explainability, complexity and fairness, among other (e.g. SHAP, LIME, Saliency Maps, Contrastive Explanations, Group and Individual Fairness Metrics, Information Criteria).
Proficiency in both written and spoken English (interviews, and all communication will be in English).
Personal qualities:
Curiosity and a strong motivation to carry out independent research
Analytical thinking and enthusiasm for interdisciplinary research and teamwork
Good communication and cooperation skills
The ability, desire and capacity to work independently, systematically, and purposefully
Orientation toward the completion of projects and the attainment of goals
Emphasis will be placed on personal suitability for the position.
Benefits:
high salary compared to international standards (532,200 NOK per year)
equipment at your disposal during employment (e.g., high-end laptop, mobile and mobile subscription)
NOK 50,000 per year to support travel to conferences and other running costs
free health insurance, travel insurance, and pension plan
strong labor laws (e.g., fully paid parental and sick leaves, 25 paid days of vacation and paid sick leave)
The application must hold:
Motivation letter for the position
Approved Diplomas and Transcripts (in Scandinavian or English language)
CV
At least two references
Master thesis
Admission to the PhD program is a requirement for taking up a position as a research fellow. The application must be submitted to School of Doctoral Studies within three months of the start date. For more information, see the Regulations relating to conditions of appointment for research fellowships: https://lovdata.no/forskrift/2024-06-28-1392/§3-19
The PhD research fellowship period is 3 years, and the earliest starting date is 01.08.2025.Working place is School of School of Economics, Innovation, and Technology. The school is located in downtown Oslo, with numerous amenities, recreational spaces, and urban fun right next door.
Kristiania University of Applied Sciences welcomes and encourages applications from diverse backgrounds. Women and persons with minority background are particularly encouraged to apply.
Only applications received through our application portal will be considered.
We use Semac background checks in our recruitment process.
The employment is to be made in accordance with the regulation 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 Kristiania.
