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Norwegian University of Science and Technology (NTNU), Department of Mechanical and Industrial Engineering
Application Deadline: April 9, 2026
Employment Type: Full-time, 3 years
Salary: NOK 550,800 per annum (Code 1017 PhD Candidate)
Supervisor: Associate Professor Chao Gao ([email protected])
Location: Trondheim, Norway
PhD in Bioinspired Materials Design and Artificial Intelligence
NTNU invites applications for a PhD position in bioinspired randomly featured materials, focusing on lightweight, damage-tolerant structures with enhanced energy absorption.
The position is part of the Materials and Manufacturing (M&M) research team and combines mechanics, materials science, and artificial intelligence to develop next-generation structural materials inspired by natural spider web architectures.
Research Focus: Bioinspired Energy-Absorbing Materials
The project explores the design principles of newly discovered “chaotic” spider webs, which exhibit unique energy dissipation mechanisms. The goal is to translate these natural design strategies into super-lightweight, high-performance engineered materials.
Key objectives include:
- Investigating spider web structures for damage tolerance and energy dissipation efficiency
- Developing a hybrid numerical and data-driven design framework
- Integrating finite element analysis (FEA) with AI-driven material optimization
- Applying deep learning and generative AI models to accelerate material design
- Creating computational tools for forward and inverse design of advanced materials
The project targets applications in aerospace, marine, and ground vehicle engineering, where strength, toughness, and lightweight performance are critical.
Duties and Responsibilities
- Participate in NTNU’s doctoral education program
- Develop hybrid numerical and AI-based methods for bioinspired material design
- Conduct independent, high-quality research
- Publish in peer-reviewed journals and present at international conferences
- Engage in international research collaborations and activities
- Contribute to research proposals and documentation
Required Qualifications
- Master’s degree in Mechanical Engineering, Engineering Mechanics, Aerospace Engineering, Data Science, or related field
- Strong academic record (equivalent to grade B or better on NTNU scale)
- Solid knowledge of finite element analysis (FEA)
- Experience with FEA software such as ABAQUS
- Hands-on experience with deep learning neural networks using PyTorch or MATLAB
- Excellent written and oral English skills
- Eligibility for admission to NTNU’s PhD Programme
Preferred Qualifications
- Background in mechanics-driven bioinspired design
- Knowledge of spider web mechanical behavior
- Experience with AI-driven forward and inverse material design
- Experience with generative AI or graph neural networks in material modeling
- Familiarity with EU or Norwegian research funding applications
- Scandinavian language skills
Candidate Profile
Successful applicants should demonstrate:
- Ability to work independently and systematically
- Strong analytical and data interpretation skills
- Curiosity and motivation for interdisciplinary research
- Flexibility in adapting research plans
- Effective communication and collaboration abilities
What NTNU Offers
- A strong international research environment
- Career development and mentoring
- Funding support for project implementation
- Access to employee benefits and pension scheme (SPK)
- Free Norwegian language training (A2 level)
- Inclusive and diverse academic culture
Employment Conditions
- 3-year doctoral appointment
- Admission to NTNU’s PhD Programme within three months of employment
- Physical presence at the institution required
- Employment subject to Norwegian State Employees Act and export control regulations
Application Requirements
Applications must be submitted electronically before April 9, 2026 and include:
- CV
- Transcripts and diplomas (Bachelor’s and Master’s)
- Master’s thesis (or draft if recently submitted)
- Project outline (max. 1500 words / 4 pages)
- Short motivation letter (max. 400 words)
- Publications or relevant research work (if applicable)
- Names and contact information of three referees
Applicants educated outside Norway must provide full documentation of degree scope and grading systems.
Contact Information
Academic inquiries:
Associate Professor Chao Gao
[email protected]
Recruitment process inquiries:
HR Senior Consultant Hedda Winnberg
This PhD position offers a unique opportunity to contribute to AI-driven bioinspired material innovation, combining advanced simulation, machine learning, and natural design principles to create next-generation lightweight structural materials.
