PhD Position in Mechanical Engineering: Physics-Informed Generative AI for Architected Materials

PhD Position in Mechanical Engineering: Physics‑Informed Generative AI for Architected Materials Deadline: December 18th 2025, 2 PM (CEST) Start Date: 1 February 2026 Funded by: The Italian Institute of Artificial Intelligence (AI4I), in collaboration with Politecnico di Milano Contact: Website: Position 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 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. 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 positions 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 modelling, and collaborative experience will make the candidate potentially competitive for roles in the next generation of AI‑driven materials discovery and design. Employment statistics of PhDs can be found at: 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 Applications for this position are managed by Politecnico di Milano . Please apply via the official PhD admissions portal. For additional information, please visit the official PhD description. About Us AI4I – The Italian Research Institute for Artificial Intelligence AI4I has been founded to perform transformative, application‑oriented research in Artificial Intelligence. AI4I is set to engage and empower gifted, entrepreneurial, young researchers who commit to producing an impact at the intersection of science, innovation, and industrial transformation. Highly competitive pay, bonus incentives, access to dedicated high‑performance computing, state‑of‑the‑art laboratories, industrial collaborations, and an ecosystem tailored to support the initiation and growth of startups stand out as some of the distinctive features of AI4I, bringing together people in a dynamic international environment. AI4I is an Institute that aims to enhance scientific research, technological