Phd Candidate In Advanced Shape Memory Materials And Additive Manufacturing

Il y a 2 jours

Maroc Université Euro-Méditerranéenne de Fès Temps plein

Gratuit avec email ou Google

Enregistrez cette offre et organisez votre recherche

Créez un compte gratuit pour enregistrer des offres d'emploi, créer des alertes et revenir à cette liste depuis votre tableau de bord.

Enregistrer le travail Enregistrer et créer une alerte

Gratuit avec email ou Google

En continuant, vous acceptez nos Conditions d’utilisation & Politique de confidentialité.

• DESCRIPTION Additive manufacturing (AM) offers unprecedented freedom to design and produce complex, multifunctional components with customized spatial and temporal responses. This research investigates process-structure-property relationships in advanced shape memory materials encompassing shape memory alloys (SMAs) and shape memory polymers (SMPs) processed via diverse AM techniques, including Selective Laser Melting / Laser Powder Bed Fusion (SLM/LPBF), Selective Laser Sintering (SLS), and Fused Deposition Modeling (FDM). By systematically varying processing parameters (e.g., laser power, scanning speed, bed temperature, and print speed), the project aims to establish local control over phase transformations, chemical composition, and microstructural grading. A core aspect of this study involves integrating machine learning algorithms to model complex, high-dimensional parameter spaces, allowing predictive optimization of thermo-mechanical behavior and shape memory effects. The ultimate goal is to establish a unified, data-driven framework for designing and fabricating functionally graded smart materials for 4D printing applications, enabling programmatic, stimulus-responsive components for biomedical, aerospace, and soft robotics systems.
• PHD STUDENT'S RESPONSIBILITIES (1) Design and execute additive manufacturing trials (LPBF/SLM, SLS, and FDM) for shape memory alloys and shape memory polymers. (2) Conduct experimental characterization of thermal, mechanical, microstructural, and shape memory properties (e.g., differential scanning calorimetry, SEM, XRD, dynamic mechanical analysis). (3) Develop machine learning models and data-driven frameworks to map multi-parameter manufacturing spaces to material response and optimization. (4) Analyze complex experimental and computational datasets to drive multi-material and multi-process innovation. (5) Prepare research findings for publication, with a target of publishing at least 4 first-author peer-reviewed journal articles during the doctoral candidacy, and present at international conferences.
• CANDIDATE PROFILE (1) Master’s degree in Materials Science Engineering, Mechanical Engineering, Polymer Engineering, Additive Manufacturing, or a related discipline. (2) Strong background in materials science, physical metallurgy, polymer science, and/or smart materials (shape memory materials). (3) Practical or theoretical knowledge of additive manufacturing techniques (SLM/LPBF, SLS, or FDM). (4) Strong interest or knowledge in machine learning, data analysis, and computational materials modeling. (5) Mandatory English proficiency (standardized test certificates such as IELTS or TOEFL are highly desirable). (6) Strong scientific writing capability and commitment to high-impact publishing.
• Apply on the university website: https://phd-cedoc.ueuromed.org/professor/subjects/87 Apllication deadline: October 25th

Amériques

Europe

Asie / Océanie

Afrique

Phd Candidate In Advanced Shape Memory Materials And Additive Manufacturing

Enregistrez cette offre et organisez votre recherche

Villes principales