Descrizione dell'offerta
PhD in Mechanical Engineering
Research Title
Physics-Informed Generative AI for Architected Materials
The Italian Institute of Artificial Intelligence (AI4I), in collaboration with Politecnico di Milano
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 . 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. Generative deep learning models to support the creation of architected materials.
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.
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 modeling, 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
Monthly net income of PhD scholarship (max 36 months): € 1.500
(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.
750 euro/month- net amount).
Teaching assistantship: availability of funding in recognition of supporting teaching activities by the PhD candidate. The PhD student is encouraged to take part in these activities, within the limits allowed by the regulations.
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.
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 Country, 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 Italy and abroad, including Competence Centers and European Digital Innovation Hubs (EDIHs).
Research Title
Physics-Informed Generative AI for Architected Materials
The Italian Institute of Artificial Intelligence (AI4I), in collaboration with Politecnico di Milano
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 . 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. Generative deep learning models to support the creation of architected materials.
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.
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 modeling, 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
Monthly net income of PhD scholarship (max 36 months): € 1.500
(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.
750 euro/month- net amount).
Teaching assistantship: availability of funding in recognition of supporting teaching activities by the PhD candidate. The PhD student is encouraged to take part in these activities, within the limits allowed by the regulations.
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.
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 Country, 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 Italy and abroad, including Competence Centers and European Digital Innovation Hubs (EDIHs).
Informazioni aggiuntive
Opportunità: PhD Position in Mechanical Engineering: Physics-Informed Generative AI for Architected Materials a Torino, Provincia di torino; piemonte
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Competenze valorizzate
- Machine Learning
- Deep Learning
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