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Chao Gao

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PhD Candidate in Bioinspired Randomly Featured Materials – Department of Mechanical and Industrial Engineering Norwegian University of Science and Technology in Norway

Degree Level

PhD

Field of study

Mechanical Engineering

Funding

Available

Deadline

Apr 10, 2026

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Country

Norway

University

Norwegian Institute of Science and Technology

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Where to contact

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Keywords

Mechanical Engineering
Materials Science
Deep Learning
Aerospace Engineering
Artificial Intelligence
Energy Absorption
Artificial Neural Network
Bio-based Materials
Mechanic
Finite Element Analysis

About this position

The Department of Mechanical and Industrial Engineering at the Norwegian University of Science and Technology (NTNU) invites applications for a PhD Candidate position in bioinspired randomly featured materials. NTNU is a leading technical-scientific university located in Trondheim, Norway, with a strong focus on professional education and research. The university hosts a vibrant community of 9,000 employees and 43,000 students, fostering knowledge creation for a better world.

This PhD position is embedded within the Materials and Manufacturing (M&M) research team and centers on developing advanced materials inspired by natural designs, particularly chaotic spider webs. The project aims to establish a hybrid numerical and data-driven design framework to create super-light, damage-tolerant materials with enhanced energy absorption. By integrating principles observed in nature, such as the unique energy dissipation mechanisms of spider webs, the research seeks to revolutionize material science for strategic fields including aerospace, marine, and ground vehicles.

The successful candidate will investigate the mechanical properties and damage-tolerance of newly discovered spider web designs, translating these findings into guidelines for high-performance materials. The project leverages artificial intelligence and deep learning to expedite the complex process of material design, utilizing tools such as ABAQUS, PyTorch, and Matlab. The research is interdisciplinary, combining mechanics, materials science, and AI-driven methodologies.

Key duties include participation in NTNU’s mandatory PhD research education programme, independent high-quality research, publication in peer-reviewed journals and international conferences, engagement with the Materials and Manufacturing research group, and involvement in international activities. The candidate will also assist in organizing and documenting research activities and proposals.

Applicants must hold a relevant Master’s degree (Mechanical Engineering, Engineering Mechanics, Aerospace Engineering, Data Science or equivalent) corresponding to a five-year Norwegian course with 120 credits at the master’s level. Master students may apply if the degree is completed before starting. A strong academic record (B or better on NTNU’s grading scale) is required, along with solid knowledge in finite element analysis and proficiency in FEA software (ABAQUS). Experience in deep learning neural networks for material design (PyTorch or Matlab) and excellent English communication skills are essential. Preferred qualifications include expertise in mechanics-driven bioinspired design, AI-driven forward and inverse design, generative AI, graph neural networks, and familiarity with EU/NFR application processes. Skills in Norwegian or another Scandinavian language are advantageous.

The position offers a gross salary of NOK 550,800 per annum, with a 2% statutory contribution to the State Pension Fund. The employment period is three years, and benefits include working capital for project implementation, free Norwegian language training at a basic level (A2), and favorable terms as a member of the Norwegian Public Service Pension Fund. NTNU provides a supportive, inclusive, and diverse working environment, with career guidance and follow-up during the PhD period.

To apply, candidates must submit their application and all required attachments electronically via Jobbnorge.no by the deadline of 10 April 2026. Required documents include transcripts and diplomas, CV, Master’s thesis or draft, project outline, motivation letter, publications, certificates, and contact information for three referees. All documents must be in English. If invited to interview, certified copies of certificates and diplomas must be provided.

For further information about the position, contact Associate Professor Chao Gao ([email protected]). For recruitment process queries, contact HR Senior Consultant Hedda Winnberg ([email protected]). NTNU encourages applications from candidates of all backgrounds and is committed to promoting equality and diversity in scientific positions.

Trondheim offers a rich cultural scene, excellent welfare services, professional subsidized day-care, international schools, and opportunities to enjoy nature, culture, and family life. NTNU’s vision is “Knowledge for a better world,” and the university strives to attract employees with diverse skills and perspectives to advance its societal mission in research and education.

Funding details

Available

What's required

Applicants must have a relevant Master's degree in Mechanical Engineering, Engineering Mechanics, Aerospace Engineering, Data Science or equivalent, corresponding to a five-year Norwegian course with 120 credits at master's level. Master students may apply but must obtain and document the degree before starting. A strong academic background is required, with an average grade of B or better on NTNU's grading scale or equivalent. Candidates with weaker grades may be considered if they can document particular suitability for PhD education. Solid knowledge in finite element analysis (FEA) and strong skills in FEA software such as ABAQUS are required. Hands-on experience in deep learning neural networks for material design using PyTorch or Matlab is necessary. Excellent oral and written English skills are required. Preferred criteria include background in mechanics-driven bioinspired design, knowledge of spider web mechanical behavior, AI-driven design, generative AI, graph neural networks, experience with EU/NFR application processes, and skills in Norwegian or another Scandinavian language.

How to apply

Submit your application and all required attachments electronically via Jobbnorge.no. Include transcripts and diplomas for Bachelor's and Master's degrees, CV, Master's thesis or draft, project outline, motivation letter, publications, certificates, and names/contact information of three referees. Ensure all documents are in English and submitted by the deadline. If invited to interview, bring certified copies of certificates and diplomas.

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