Postdoc: Bayesian Inverse Problems & Uncertainty Quantification

University of Oulu; Oulu; On-site; EUR 44,000 - 52,000; Full time

Benefits offered by this job

Wellness benefit ePassi

Buddy Programme

Spouse Network support

HR Excellence in Research label

Flexible work-life balance

Live in Oulu

Job summary

The University of Oulu, in the Research Group on Computational Uncertainty Quantification, invites applications for a Postdoctoral Researcher position. The role focuses on Bayesian inverse problems, uncertainty quantification, and development of new priors with scalable computation.

You will contribute to research software in Python, work with international collaborators, and supervise undergraduate and graduate students while advancing mathematical science.

Qualifications

• PhD in mathematics or closely related field completed by closing date.
• Strong mathematical background with analysis focus.
• Ability to perform independent scientific research.
• Teaching skills for the position.
• Fluent written and spoken English.

Responsibilities

• Conduct independent and collaborative research in applied mathematics, focusing on Bayesian inverse problems and computational uncertainty quantification.
• Develop and analyse new classes of Bayesian priors for inverse problems, including their properties and computation.
• Develop methods for exploring high- to infinite-dimensional posterior distributions.
• Contribute to research software development, especially in Python.
• Collaborate with national and international partners and supervise students.

Skills

Python

Mathematical analysis

Research

Independent research

Education

Doctoral degree in mathematics or closely related field

Tools

Python

Job description

The University of Oulu, in the Research Group on Computational Uncertainty Quantification, invites applications for a Postdoctoral Researcher position. The role focuses on Bayesian inverse problems, uncertainty quantification, and development of new priors with scalable computation.

You will contribute to research software in Python, work with international collaborators, and supervise undergraduate and graduate students while advancing mathematical science.