Researcher recruitment
- 02/04/2025
RESEARCHER RECRUITMENT
Regarding the project:
Generative inverse design of bio-inspired TPMS porous structures: From generative AI, multiscale topology optimization to design and applications
- Positions: 02 researchers
- Workplace: CIRTech Institute, HUTECH University, Vietnam
- Last application date: 31/05/2025 or when fully occupied
- Vacancy rate: 100%
Project description:
This project focuses on one of the outstanding bio-inspired structures, the triply periodic minimal surface (TPMS) structure, and highlights its robustness in practical problems through topology optimization. These structures, derived from the zero-mean-curvature characteristic of minimal surfaces, exhibit numerous applications including biomedical, aerospace, transportation, construction, etc. This structural group can have a great geometrical variety, indicated by their unlimited combinations of TPMS types (e.g., Primitive, Gyroid, Diamond), solid types (e.g., network-based, sheet-based), and solid variants (e.g., functional grading, hybrid). This project develops a novel data-driven approach based on mathematical computation and generative inverse design of TPMS structures. This method greatly overcomes the inaccuracy and uncontrollability associated with current meshing methods. Integrating generative AI (GenAI) into TPMS structures can enable optimal and inverse designs for new TPMS-based structures for various engineering applications, such as strength, lightweight, and energy absorption.
Requirements:
This project focuses on one of the outstanding bio-inspired structures, the triply periodic minimal surface (TPMS) structure, and highlights its robustness in practical problems through topology optimization. These structures, derived from the zero-mean-curvature characteristic of minimal surfaces, exhibit numerous applications including biomedical, aerospace, transportation, construction, etc. This structural group can have a great geometrical variety, indicated by their unlimited combinations of TPMS types (e.g., Primitive, Gyroid, Diamond), solid types (e.g., network-based, sheet-based), and solid variants (e.g., functional grading, hybrid). This project develops a novel data-driven approach based on mathematical computation and generative inverse design of TPMS structures. This method greatly overcomes the inaccuracy and uncontrollability associated with current meshing methods. Integrating generative AI (GenAI) into TPMS structures can enable optimal and inverse designs for new TPMS-based structures for various engineering applications, such as strength, lightweight, and energy absorption.
Requirements:
- Master degree in Materials, Civil, Mechanical Engineering, Applied Mathematics, Computer Science, or equivalent degrees;
- Experience with Applied Math, AI, Finite Elements;
- Fluent in English (IELTS or equivalent);
- Fluent in programming languages.
Benefits:
- Competitive salary;
- Bonuses based on KPI;
- Short research stays at RUB University, Germany;
- Master and PhD scholarships at top 500 universities (according to Times Higher Education).
- 01 CV with the contact details of at least one reference;
- 01 Letter of motivation explaining your vision toward the research topic.
The physical interview will take place at HUTECH University when your profile is accepted. Detailed information will be sent to applicants via email.
Project coordinators:
- Prof. Hung Nguyen-Xuan (HUTECH)
- Prof. Klaus Hackl (RUB)
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