Data and Decision Science

The application deadline is 15 February 2026

Apply here

Specialisation objects

The PhD specialization in Data and Decision Science prepares candidates for careers in the world’s leading academic institutions, research-oriented international and national organizations, and the industry. We encourage candidates with strong quantitative and analytical skills and background in areas in decision science relevant to the specialisation to apply. These areas includes logistics, retail, energy, finance and economics, where modern AI innovations enhance management decisions.   

Distinguishing features of the specialisation

• The specialisation is built on a unique collaboration between data science and operations research. 
• PhD-candidates are actively involved in a wide range of internationally-oriented networks and research centers, such as AMOR, SURE-AI and NORA.
• There are close relationships with relevant industry partners in the specialisation, offering the PhD-candidates exciting opportunities for joint research ventures.    

Fully funded scholarships

All PhD candidates receive financial support when accepted into the programme. The candidates are hired as full-time employees on an initial four-year contract. Continuation of the support through the four years of the programme is dependent on good standing and regular progress towards completing the programme’s requirements. PhD candidates are entitled to full parental leave and health insurance, and are part of the Norwegian Public Service Pension Fund. The workplace is BI Norwegian Business School at its main campus in Oslo.

What you can expect

The four-year study programme leading to a PhD degree is designed to allow you to conduct in-depth research. In addition, it is comprised of a course component, seminars, PhD committees, pre-doctoral defence, and lastly, dissertation and final defence. 25% of the time is reserved for teaching.

The Department

The Department of Data Science and Analytics, where the candidates will be based, counts 13 faculty members. The Department is committed to excellent research at the highest international level. Faculty interests span a wide range of fields in modern data science and business analytics with a strong quantitative emphasis, and they are innovating in artificial intelligence that impacts core business areas. The Department is international in its composition and orientation. It maintains close connections with industry and public sector, including unique collaborations within retail, shipping and energy. 

Areas of research

 The Department’s faculty members are actively engaged in academic research. Without being exhaustive, the following list of research areas covers some of the main research activities the Department of Data Science and Analytics: 

• Knowledge representation and reasoning, (multi-agent) decision making under uncertainty.
• Probabilistic programming and probabilistic graphical models. 
• Reinforcement learning, dynamic programming and distributionally robust and risk-sensitive optimisation. 
• Deep generative modeling and multimodal learning.
• Business applications of machine learning and natural language processing to classification, forecasting, anomaly detection and operation management, in the areas of logistics, retail, energy, finance and economics.
• Neuronal dynamical systems in finance and energy.
• Stochastics and rough analysis of time series data.
• Bayesian decision theory, inference, econometrics and statistics.
• Explainable and ethical AI.
• Sustainable AI and AI for sustainability.

The application deadline is 15 February 2026

Apply here