PhD in Generative AI and Statistics: Coalescent-inspired diffusion models for discrete data University of Oslo in Norway

Call for applications for a fully funded PhD in Generative AI and Statistics at the University of Oslo, hosted by Integreat – Norwegian Centre for Knowledge-driven Machine Learning. The project is titled Coalescent-inspired diffusion models for discrete data and sits at the intersection of computer science, statistics, mathematics, and biology.

The research focuses on building next-generation generative AI models for discrete data such as DNA, RNA, and proteins. The PhD will combine diffusion models, probability and statistics, and coalescent theory from genetics. The successful candidate will develop new theory and algorithms, build scalable implementations for discrete sequence data, and apply the methods to statistical genetics.

Applicants should hold a master’s degree in Machine Learning/AI, Statistics, Mathematics, Computer Science, Physics, or a related quantitative field. A strong background in probability and statistics, linear algebra, and programming is expected, with skills in Python, PyTorch, or JAX especially relevant. Preferred extras include experience with Bayesian statistics, stochastic processes, diffusion models, and transformer models.

The position is fully funded for 3–4 years and includes a salary of NOK 550,800–595,000 per year. The post also mentions an optional 4th year for teaching/research, structured training and career development, international collaboration, and research mobility funding for international stays.

To apply, prepare a motivation letter, CV, academic transcripts, publication list if available, and contact details for 2–3 referees. The deadline is 11 May 2026.