Questa posizione è in Leonardo
Riassunto dell'opportunità da parte della Joinrs AI: Leonardo cerca uno studente giovane in discipline STEM per un tirocinio finalizzato alla tesi su simulazioni CFD ad alta fedeltà su infrastrutture HPC, con tutor dedicati e opportunità di crescita in un contesto industriale internazionale. L’esperienza è ibrida presso il sito di Genova Fiumara e include la possibilità di viaggi nazionali.
Il processo di selezione sarà interamente gestito da Leonardo.
Leonardo is an international industrial group, among the world's leading companies in Aerospace, Defense and Security, creating multi-domain technological capabilities in Helicopters, Aircraft, Aerostructures, Electronics, Cyber Security and Space. With over 60,000 employees worldwide, the company has a strong industrial presence in Italy, the United Kingdom, Poland, the United States, and operates in 150 countries also through subsidiaries, joint ventures and participations. A protagonist of the main global strategic programs, it is a technological and industrial partner of Governments, Defense Administrations, Institutions and companies.
If you are enrolled in a University, are in your final year of a Master's degree and need to write a thesis in STEM disciplines, Leonardo offers you the opportunity to strengthen your academic path through an experience in the company.
Expert tutors in their sector will follow you, allowing you to deepen the theoretical part and develop your thesis, preparing you in the best possible way for future professional challenges.
The topics proposed for theses to be carried out at Leonardo embrace a vast spectrum of technological, research and innovation areas: from Artificial Intelligence to High-Performance Computing, from Cyber Security to Materials Engineering, passing through the aerospace sectors. You will be able to explore the most avant-garde areas of your field of study, with creativity and a spirit of innovation.
We are looking for 1 young student for the Genoa Fiumara site to be included in an internship with the aim of developing their thesis on the topic of high-fidelity Computational Fluid Dynamics (CFD) simulations on HPC infrastructures on the subject:
- Assessment of numerical prediction capabilities of high fidelity CFD GPU-accelerated codes for simulation of wing-body junctions in transonic regime.
The study focuses on the simulation of the wing-fuselage junction using high-fidelity Computational Fluid Dynamics numerical techniques, using HPC (High Performance Computing) resources currently integrated into industrial workflows. The goal is to validate the computational efficiency and physical accuracy of such tools to accelerate modern aeronautical design.
Education:
Bachelor's degree in STEM disciplines, with an interest in the world of engineering and computer science.
Seniority:
Junior
Behavioral skills:
- Proactivity;
- Ability to work in a team;
- Learning orientation;
- Flexibility.
Language skills:
Advanced knowledge of the English language, level B2-C1.
Computer skills:
- Basic/intermediate knowledge about parallel computing,
- numerical analysis and algorithms for PDE solution.
- Proficiency in at least one major HPC CFD software package, with a strong preference for open-source platforms
- Main programming languages: C++, Python
Other:
Availability to make short national trips.
How does the selection process work?
Following the collection of applications, the CVs most in line with the requested requirements are evaluated and identified.
Selected candidates will have an introductory interview with the Human Resources team and with the Business, where technical topics, motivation and personal attitudes will be explored.
At the end of the process, the candidate receives feedback, both in case of a positive and negative outcome.
We look forward to receiving your application.
Collaborating with us you will constantly confront the challenges of high technology, increase your skills and build an excellent professional path.
Seniority:
Junior
Primary Location:
IT - Genova - Fiumara
Contract Type:
Hybrid Working:
Hybrid