Efficient PDE Solvers & Data-Driven Modeling (PINNs)

Italian Ministry of Education, University and Research; Italia; On-site; EUR 30,000 - 45,000; Full time

Job summary

Sapienza University of Rome, Department of Mathematics, invites applications for a research position focused on numerical analysis and mathematical modelling.

The role emphasises development and analysis of efficient numerical methods for ordinary and partial differential equations, with potential work on model order reduction, optimal control for dynamical systems, and data-driven approaches including PINNs.

Qualifications

• PhD in mathematics or a closely related field.
• Experience in numerical analysis of ODE/PDEs.
• Strong background in modeling and computational methods.
• Ability to carry out independent research and collaboration.

Responsibilities

• Conduct research in numerical analysis and mathematical modelling for ODEs/PDEs.
• Develop and analyse efficient numerical methods for equations and systems.
• Explore model order reduction, optimal control, and data-driven approaches including PINNs.
• Contribute to dissemination of results and collaboration within the department.

Skills

Numerical analysis

Mathematical modelling

Model order reduction

Optimal control

Data-driven methods

Machine learning

PINNs

Education

PhD in Mathematics or closely related field

Job description

Sapienza University of Rome, Department of Mathematics, invites applications for a research position focused on numerical analysis and mathematical modelling.

The role emphasises development and analysis of efficient numerical methods for ordinary and partial differential equations, with potential work on model order reduction, optimal control for dynamical systems, and data-driven approaches including PINNs.