PhD Posizione in Mechanical Engineering: AI-Guided Design of Programmable Intelligent Metamaterials at The Italian Institute of Artificial Intelligence

Posizione	PhD Posizione in Mechanical Engineering: AI-Guided Design of Programmable Intelligent Metamaterials
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: AI-Guided Design of Programmable Intelligent Metamaterials. If the PhD Posizione in Mechanical Engineering: AI-Guided Design of Programmable Intelligent Metamaterials 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: AI-Guided Design of Programmable Intelligent Metamaterials sia in linea con le tue qualifiche.

PhD in Mechanical Engineering

Research Title

AI-Guided Design of Programmable Intelligent Metamaterials

Deadline

The 1st of July 2026

Funded by

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

Supervisors

Marco Maurizi (AI4I)

Valentina Zega (Politecnico di Milano)

Contacts

Websites

R&D Labs - AI4I

SCHEDA_5424_ISSG_AI-GUIDED_DESIGN_OF_PROGRAMMABLE.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. The emergence of intelligent and re-programmable metamaterials — engineered systems whose functional properties arise from geometry and architecture rather than chemistry alone — marks a paradigm shift in how materials interact with their environment. Unlike conventional materials with fixed, intrinsic behavior, these metamaterials can sense external stimuli, process information, and dynamically modify their response in real time. They embody a new class of programmable matter, where structural geometry and embedded functionality combine to achieve adaptive mechanical, acoustic, or electromechanical performance

Such systems hold great promise in fields ranging from vibration and noise control to wearable haptics, soft robotics, and human–machine interfaces. However, the design and control of architectures capable of robust, reversible reconfiguration remain unsolved challenges.

Research Methods and Techniques

The research will combine machine learning, multi-physics simulation, and additive manufacturing in an integrated workflow for designing and realizing re-programmable metamaterials. Key methodologies could include:

Generative deep learning models (Graph Neural Networks, Diffusion Models, Transformers) to explore design spaces and synthesize architectures with tunable mechanical or electromechanical responses

Physics-informed and multi-objective optimization frameworks, coupling finite-element simulations with AIbased surrogates to enable rapid evaluation and tuning of programmable states

Embedding actuation and sensing mechanisms within the geometric design process, supporting heterogeneous architectures that combine passive load-bearing elements with active functional layers or distributed control nodes

Integration of Large Language Models (LLMs) to assist in translating high-level functional specifications (e.g., “attenuate vibrations in the frequency range 1-10 kHz”) into parametric design constraints

Closed-loop digital workflows that connect AI design, simulation feedback, and experimental data for model-based re-programming of the fabricated metamaterial

Additive manufacturing and testing of physical prototypes — such as intelligent vibration absorbers, adaptive haptic surfaces, or acoustically tunable structures — to validate their real-time programmability. Through this synergy between AI-driven design, embedded intelligence, and real-time control, the project will establish the foundations for programmable metamaterials capable of switching functions or adapting to changing environments on demand

Educational Objectives

The doctoral candidate will develop both specialized expertise in intelligent metamaterials and broad scientific and problem-solving skills essential for independent research.

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: AI-Guided Design of Programmable Intelligent Metamaterials
Luogo di lavoro: Italia
Paese: IT

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