PhD Posizione in Mechanical Engineering: Physics-Informed Generative AI for Architected Materials at The Italian Institute of Artificial Intelligence

Posizione	PhD Posizione in Mechanical Engineering: Physics-Informed Generative AI for Architected Materials
Pubblicato	20 Jun 2026
Scaduto	20 Jul 2026
Azienda	The Italian Institute of Artificial Intelligence
Località	Italia \| IT
Contratto	Full Time

Descrizione del lavoro:

Ultime informazioni sul lavoro da The Italian Institute of Artificial Intelligence per la posizione di PhD Posizione in Mechanical Engineering: Physics-Informed Generative AI for Architected Materials. If the PhD Posizione in Mechanical Engineering: Physics-Informed Generative AI for Architected Materials vacante in Italia corrisponde al tuo profilo, invia il tuo CV aggiornato direttamente tramite il portale Jobkos.

Tieni presente che candidarsi per un lavoro richiede tempo, poiché i candidati devono soddisfare determinati requisiti aziendali. Speriamo che l'opportunità presso The Italian Institute of Artificial Intelligence per la posizione di PhD Posizione in Mechanical Engineering: Physics-Informed Generative AI for Architected Materials sia in linea con le tue qualifiche.

PhD in Mechanical Engineering

Research Title

Physics-Informed Generative AI for Architected Materials

Deadline

The 1st of July 2026

Funded by

The Italian Institute of Artificial Intelligence (AI4I), in collaboration with Politecnico di Milano

Websites

R&D Labs - AI4I

SCHEDA_5470_MECC_PHYSICS-INFORMED_GENERATIVE_AI_FOR.PDF

Posizione Description

The PhD scholarship is funded by the Italian Institute of Artificial Intelligence (AI4I). The research will be carried out jointly at AI4I and Politecnico di Milano. The project focuses on architected materials, also known as metamaterials.

Architected materials are engineered systems whose exceptional properties originate from geometry rather than chemistry alone. By computationally designing their internal structure across scales, these materials can display unconventional mechanical, acoustic, or multifunctional behaviors. Recent advances in artificial intelligence (AI) and generative modelling have created new opportunities to accelerate their design and broaden the space of feasible, manufacturable architectures. Data-driven approaches now enable the integration of heterogeneous requirements — from geometric and manufacturing constraints to target mechanical responses and multifunctional performance.

Within this context, the PhD project aims to develop foundation models for the design of architected materials. The main objective is to uncover new or unconventional physical behaviors and establish a unified framework for the design of high-performing, manufacturable metamaterials.

Research Methods and Techniques

The research will integrate physics-based simulation, generative AI, and formal representations of material architectures to develop a new class of models for the design of architected materials. Potential applications include vibration attenuation, impact protection, and acoustic filtering.

Key methodologies could include:

Generative deep learning models to support the creation of architected materials.
Unified graph and geometric encodings to incorporate design requirements.
Physics-informed pretraining on large-scale numerical datasets.
Multi-objective and multi-physics frameworks to enable inverse design of architected metamaterials.

Experimental validation through fabrication and testing of prototypes or samples.

Educational Objectives

The PhD candidate will develop a strong interdisciplinary background spanning artificial intelligence, computational mechanics and modelling, engineering design, materials science, and manufacturing. In addition, the candidate will enhance soft skills such as scientific writing, communication, and problem-solving.

The candidate will learn to develop and apply generative and physics-informed machine learning methods for the design of materials and structures. Expertise will be gained in multi-physics modelling and simulation of architected materials, as well as in dataset generation, curation, and model training. The candidate will further strengthen the ability to create, disseminate, and communicate scientific knowledge, and to work effectively within an international research environment.

Job Opportunities

The scholarship offers immersion in a multidisciplinary and international research ecosystem, involving collaboration with leading AI scientists and potentially also industrial partners.

Career opportunities could span across research, industry, and technology innovation, where AI and materials design converge. Successful candidates will develop competencies that could be exploited in academic and research Posiziones in computational materials science, mechanics, and AI for engineering design. Potential industrial fields of interest concerning this topic can be aerospace, automotive, and digital manufacturing, among others.

The combination of AI expertise, physical modeling, and collaborative experience will make the candidate potentially competitive for roles in the Succ generation of AI-driven materials discovery and design.

Employment statistics of PhDs can be found

Scholarships and Financial support

Monthly net income of PhD scholarship (max 36 months): € 1.500

(In case of a change of the welfare rates during the three-year period, the amount could be slightly modified)

Additional Support

Financial aid is available for all PhD candidates (purchase of study books and materials, funding for participation in courses, summer schools, workshops and conferences) for a total amount of € 6.114,50.
Our candidates are strongly encouraged to spend a research period abroad, joining high-level research groups in the specific PhD research topic, selected in agreement with the Supervisor.
An increase in the scholarship will be applied for periods up to 6 months (approx. 750 euro/month- net amount).
Teaching assistantship: availability of funding in recognition of supporting teaching activities by the PhD candidate. There are various forms of financial aid for activities of support to the teaching practice. The PhD student is encouraged to take part in these activities, within the limits allowed by the regulations.

What We Offer

A stimulating, ambitious and collaborative research environment within AI4I’s and Politecnico di Milano’s international, interdisciplinary ecosystem.
The opportunity to co-author high-impact publications and help define emerging paradigms in AI-guided materials design.
Tailored mentoring to support your long-term academic or industry career trajectory.
Access to high-performance computing (HPC) infrastructure and state-of-the-art fabrication and testing facilities.
Opportunities for international collaborations (e.g. UC Berkeley, Penn State, Imperial College London).

How to Apply

To be considered, applications must be submitted exclusively through the official Politecnico di Milano application page:

Chi Siamo

AI4I – The Italian Research Institute for Artificial Intelligence

AI4I is an Institute that aims to enhance scientific research, technological transfer, and, more generally, the innovation capacity of the Paese, promoting its positive impact on industry, services and public administration. To this end, the Institute contributes to creating a research and innovation infrastructure that employs artificial intelligence methods, with particular reference to manufacturing processes, within the framework of the Industry 4.0 process and its entire value chain. The Institute establishes relationships with similar entities and organizations in Italia and abroad, including Competence Centers and European Digital Innovation Hubs (EDIHs).

Website:

Info sul lavoro:

Azienda: The Italian Institute of Artificial Intelligence
Posizione: PhD Posizione in Mechanical Engineering: Physics-Informed Generative AI for Architected Materials
Luogo di lavoro: Italia
Paese: IT

Come inviare la candidatura:

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