Research Position in Computational Mechanics and Scientific Machine Learning at SISSA, Italy

The International School for Advanced Studies (SISSA), Trieste, Italy, invites applications for a Research Contract Position in the Mathematics Area under the prestigious FIS 3 ROSA Advanced Grant project. The successful candidate will contribute to cutting-edge research in model reduction, surrogate modeling, scientific machine learning, computational mechanics, and high-performance computing for complex engineering and scientific applications.

This two-year research appointment offers an excellent opportunity to work with internationally recognized researchers on advanced numerical methods, digital twins, data-driven modeling, and scientific computing technologies.

Research Position in Computational Mechanics and Scientific Machine Learning at SISSA, Italy

Summary Table

Designation

Research Contract Holder (Postdoctoral Researcher)

Research Title:
Model Reduction and Surrogate Methods for Applications in Computational Mechanics

Research Area

The selected researcher will work in advanced areas including:

• Scientific Computing
• Numerical Analysis
• Computational Mechanics
• Computational Fluid Dynamics (CFD)
• Scientific Machine Learning
• Reduced Order Modeling (ROM)
• Data Science and Data Assimilation
• Uncertainty Quantification
• Digital Twins
• Artificial Neural Networks
• High-Performance Computing (HPC)
• Large-Scale Scientific Computing
• Optimization and Control
• Fluid-Structure Interaction
• Multiphase Flow Modeling

Location

SISSA – International School for Advanced Studies
Trieste, Italy

A relocation contribution is available for successful candidates relocating from abroad (EU and non-EU countries).

Eligibility / Qualification

Required Education

Applicants must possess:

Master’s Degree in one of the following fields:

• Mathematical Engineering
• Biomedical Engineering
• Industrial Engineering (Mechanical, Aerospace, Energy, Nuclear, etc.)
• Physical Engineering
• Civil Engineering
• Mathematics
• Physics
• Computer Science
• Computer Engineering
• Data Science
• Scientific Computing
• Equivalent disciplines

PhD Degree in:

• Applied Mathematics
• Computational Sciences
• Computational Engineering
• Numerical Analysis
• Related disciplines

Required Experience

Candidates should demonstrate experience in:

• Mathematical Modeling
• Numerical Simulation of Complex Systems
• Computational Mechanics
• Optimization and Control
• Data Science and Machine Learning
• Data Assimilation
• Uncertainty Quantification
• Scientific Computing Programming
• High-Performance Computing
• Large-Scale Computing
• Computer Graphics

Technical Skills

Strong knowledge of:

• Python
• C/C++
• Scientific Computing Libraries
• Reduced Basis Methods
• Proper Orthogonal Decomposition (POD)
• Geometric Parametrization Techniques
• Digital Twin Technologies
• Artificial Intelligence and Neural Networks

Experience with the following software frameworks is highly desirable:

• ITHACA
• RBniCS
• multiphenics
• PyGeM
• PyDMD
• EZyRB
• ATHENA
• PINA

Job Description

The selected researcher will:

• Develop advanced surrogate and reduced-order models for computational mechanics applications.
• Conduct research in scientific machine learning and data-driven simulation.
• Work on numerical methods for fluid dynamics and complex systems governed by PDEs.
• Contribute to digital twin development and uncertainty quantification methodologies.
• Design and implement high-performance scientific computing solutions.
• Participate in software development, maintenance, and dissemination of ROM-related libraries.
• Collaborate with an interdisciplinary research team under the ROSA project.
• Prepare research reports and scientific publications.

Research activities will be conducted within the project:

ROSA – Reduced Order and Surrogate Methods for Advanced Applications
(FIS 3 ROSA Advanced Grant, FIS-2024-07504)

Application Process

Applicants must submit:

1. Online application form.
2. Updated Curriculum Vitae.
3. Valid identification document.
4. A short research proposal (maximum 5 pages).
5. Research proposal abstract.
6. Academic qualifications and supporting documents.
7. Publications and research outputs (if applicable).
8. Reference letters submitted by referees.

Application Portal

Applications must be submitted through the SISSA online recruitment system:

Selection Process

Applications will be evaluated on a 100-point scale:

Minimum qualifying score: 70/100

Interviews, if required, may be conducted online.

Salary & Benefits

• Gross annual salary: €32,000
• Paid in 13 monthly installments
• Workplace accident and liability insurance
• Opportunity to work within an internationally recognized research group
• Relocation support for international candidates
• Access to advanced computational research infrastructure

Research Team

The successful candidate will join the research group led by:

Scientific Supervisor: Prof. Gianluigi Rozza

Research Team Members:

• Federico Pichi
• Niccolò Tonicello
• Pasquale Africa
• Antonio Colanera
• Nicola Demo
• Pierfrancesco Siena
• Davide Oberto

How to Apply

1. Prepare all required application documents.
2. Draft a research proposal (up to 5 pages) aligned with the advertised research themes.
3. Complete the online application via the PICA platform.
4. Upload all required documents before the deadline.
5. Ensure referees submit recommendation letters before the reference letter deadline.

Last Date for Apply

Application Deadline

15 June 2026 (11:59 PM CEST, Rome Time)

Reference Letter Deadline

17 June 2026 (11:59 PM CEST, Rome Time)

Applications submitted after the deadline will not be accepted.

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