PhD Researcher: AI-Driven 4D Metamaterials for Spatio-Temporal Mechanotransduction
Develop AI-designed 4D metamaterials to revolutionize adaptive biomedical implants for tissue regeneration and infection prevention.
Best for:Best for materials science PhD candidates with expertise in computational design, biomaterials, and interdisciplinary research at the intersection of AI and regenerative medicine.
Overview
This PhD position at the Institut de Science des Matériaux de Mulhouse (IS2M) focuses on pioneering AI-driven 4D metamaterials with gyroid geometries to dynamically orchestrate mechanotransduction in regenerative medicine. Under the co-supervision of Laurent Pieuchot (CNRS) and André Castro (Universidade de Lisboa), the project integrates machine learning for inverse design, nanocomposite formulation, and two-photon stereolithography fabrication. The goal is to create self-adjusting implants that autonomously respond to physiological microenvironments, enabling closed-loop tissue regeneration and antimicrobial activity. The research bridges materials science, bioengineering, and computational modeling, with collaborative opportunities at both IS2M and Técnico Lisboa.
What you'll do
- Design and develop AI algorithms for inverse engineering of triply periodic minimal surfaces (TPMS) with gyroid geometries.
- Formulate and characterize nanocomposite resins based on polycaprolactone (PCL) with antimicrobial nanozeolites and mesoporous fillers.
- Fabricate submicron-scale 4D metamaterials using two-photon stereolithography on the DIADEM platform.
- Investigate the mechanobiological response of stem cells to dynamically curving surfaces, focusing on YAP/TAZ pathway activation.
- Collaborate with partners at Instituto Superior Técnico (Lisbon) for computational modeling and experimental validation.
- Publish findings in high-impact journals and present results at international conferences.
- Contribute to interdisciplinary workshops and training programs at IS2M and Técnico Lisboa.
Requirements
Degree required: Master's degree (or equivalent) in Materials Science, Bioengineering, Chemical Engineering, or a related discipline.
Degree offered: PhD
Language: Fluent English (written and spoken) for collaboration and publication; French proficiency is not required but may be advantageous for local integration.
Instruction: English (thesis, supervision, and collaboration with Técnico Lisboa); French may be used for internal communication at IS2M.
- Proven expertise in computational materials design or machine learning for scientific applications.
- Experience with polymer chemistry or nanocomposite formulation.
- Familiarity with advanced fabrication techniques (e.g., two-photon stereolithography).
- Strong background in cell biology or mechanobiology.
- Proficiency in scientific programming (Python, MATLAB, or similar).
- Ability to conduct experimental characterization of biomaterials (e.g., mechanical testing, microscopy).
- No nationality restrictions; open to international applicants.
- No age limit specified.
- No prior experience caps; open to all applicants with relevant qualifications.
Funding & terms
How to apply
Deadline: 2026-10-19
Applicants must submit their CV, a cover letter detailing their research interests and motivation, and academic transcripts through the CNRS employment portal. A research proposal outlining how the candidate’s background aligns with the project’s objectives is also required. Shortlisted candidates may be invited for an interview.
- CV
- Cover letter
- Academic transcripts (BSc and MSc)
- Research proposal (1-2 pages)
- Proof of English proficiency (if applicable)
Contact
CNRS Employment Office· Recruitment Contact
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