PhD Candidate in AI-driven smart material characterisation and modelling

Norwegian University of Science and Technology (NTNU); Trondheim; In loco; NOK 522.000 - 638.000; Tempo pieno

Vantaggi offerti da questo lavoro

Mentor programme

Pension fund (SPK)

Open and inclusive environment

Career guidance

Descrizione del lavoro

Norwegian University of Science and Technology (NTNU) invites applications for a PhD Candidate position focused on AI-driven smart material characterisation and modelling within the AIMOS project. The research spans experimental work and computational modelling for adaptive offshore structures, with emphasis on stiffness, response times, and long-term durability.

The role combines experimentation, physics-informed modelling, and AI, under the Head of Department, and offers a path into

Competenze

• Master's degree in mechanical engineering, computer science, or equivalent (five-year Norwegian course).
• Admission to NTNU's doctoral program before 2027.
• Very good English skills (written and spoken).
• Non-English country applicants must show official language test.

Mansioni

• Take courses totaling at least 30 ECTS.
• Conduct high-quality research within AIMOS scope.
• Publish academic papers and popular science pieces.
• Collaborate with AIMOS PhD candidates on AI and fluid-structure topics.
• Join and contribute to the SIMLab research group.

Conoscenze

Python

Finite-Elements

AI methods

Formazione

Master's degree

Strumenti

Python

Descrizione del lavoro

About The Position

Would you like to work at the intersection of artificial intelligence, material science, and offshore engineering, contributing to the development of the next generation of intelligent and adaptive offshore structures? The Department of Structural Engineering at NTNU has a vacancy for a PhD Candidate in AI-driven smart material characterisation and modelling. The position is part of the AIMOS project (Artificial Intelligence for Multiscale Offshore Structures), which develops integrated AI methods for the analysis, design, monitoring, and control of floating offshore systems.

The PhD project focuses on the experimental characterisation and computational modelling of smart materials with potential applications in adaptive offshore structures. These materials offer new opportunities for developing structural systems capable of actively responding to changing environmental and operational conditions. A central challenge is to understand and predict their mechanical behaviour, including stiffness variations, response times, and long-term durability, while developing computationally efficient models suitable for structural simulations. The candidate will combine experimental investigations, physics-informed modelling, and artificial intelligence to establish predictive material models and evaluate the feasibility of smart-material-based actuation in offshore structures. The position offers the opportunity to conduct cutting-edge research at the intersection of material mechanics, artificial intelligence, and offshore engineering, contributing to the development of more adaptive and resilient marine infrastructure. Your immediate leader will be the Head of Department.

About The Position

Would you like to work at the intersection of artificial intelligence, material science, and offshore engineering, contributing to the development of the next generation of intelligent and adaptive offshore structures? The Department of Structural Engineering at NTNU has a vacancy for a PhD Candidate in AI-driven smart material characterisation and modelling. The position is part of the AIMOS project (Artificial Intelligence for Multiscale Offshore Structures), which develops integrated AI methods for the analysis, design, monitoring, and control of floating offshore systems. The PhD project focuses on the experimental characterisation and computational modelling of smart materials with potential applications in adaptive offshore structures. These materials offer new opportunities for developing structural systems capable of actively responding to changing environmental and operational conditions. A central challenge is to understand and predict their mechanical behaviour, including stiffness variations, response times, and long-term durability, while developing computationally efficient models suitable for structural simulations. The candidate will combine experimental investigations, physics-informed modelling, and artificial intelligence to establish predictive material models and evaluate the feasibility of smart-material-based actuation in offshore structures. The position offers the opportunity to conduct cutting-edge research at the intersection of material mechanics, artificial intelligence, and offshore engineering, contributing to the development of more adaptive and resilient marine infrastructure. Your immediate leader will be the Head of Department.

Duties of the position

• Take courses in relevant technical topics, comprising a minimum of 30 ECTS.
• Carry out research of good quality within the framework described above
• Academic publications and popular science dissemination
• Collaborate with other PhD candidates in AIMOS project, working with fluid-structure interaction and agentic AI.
• Participate in the SIMLab research group at the department

Be prepared for changes to your work duties after employment.

Required Selection Criteria

• You must have a relevant Master's degree in mechanical engineering, computer science, or equivalent. Your course of study must correspond to a five-year Norwegian course, where 120 credits have been obtained at master's level. Master students can apply, but the master's degree must be obtained and documented before starting the position and no later than 01.01.2027.
• You must have a strong academic background from your previous studies and have an average grade from your Master's degree study, or equivalent education, which is equal to B or better compared to NTNU's grading scale. If you do not have letter grades from previous studies, you must have an equally good academic foundation. If you have a weaker grade background, you may be considered if you can document that you are particularly suitable for a PhD education.
• You must meet the requirements for admission to the faculty's doctoral program (https://www.ntnu.edu/studies/phiv)
• Very good English skills (both written and spoken)
• Applicants from non-English speaking countries outside Europe must present an official language test report. The acceptable tests are TOEFL, IELTS, and Cambridge Certificate in Advanced English (CAE) or Cambridge Certificate of Proficiency in English (CPE). Minimum scores are:
  • TOEFL: 600 / writing 4.5 (paper-based) or 92 / writing 22 (internet-based)
  • IELTS: 6.5, with no section lower than 5.5 (only Academic IELTS test accepted)
  • CAE/CPE: grade B or A.

The appointment is to be made in accordance with NTNUs guidelines for recruitment positions for general criteria for the position.

Preferred Selection Criteria

• Strong background in mechanical, or structural engineering disciplines, including material mechanics
• Solid knowledge of finite-element analyses, computational plasticity
• Strong programming skills in Python
• Experience with AI and data-driven methods, such as machine learning applied to engineering problems
• Experience with experimental work or data analysis

Personal characteristics

• Work independently and in structured way, as well as collaboratively within an interdisciplinary team.
• Have good communication skills, able to present and discuss your research with other professionals
• Get involved and contribute constructively with feedback
• Work constructively under pressure or in the face of adversity
• Show curiosity and a strong motivation for the subject
• Analyse data, assess different perspectives and draw well-founded conclusions
• Be flexible and open to adjusting the plan for the project as needed

Emphasis will be placed on personal qualities.

We offer

• An exciting job with an important mission in society
• Developing tasks in a strong and international professional environment
• Career guidance and follow-up during the PhD period
• Open and inclusive working environment with committed colleagues
• Working capital that can be used to implement the project
• Mentor programme as a new employee at NTNU
• Favourable terms as a member of the Norwegian Public Service Pension Fund (SPK)

As a PhD Candidate at NTNU, you will have access to employee benefits.

Diversity

Diversity is a strength, and at NTNU we aim to be an employer that reflects the diversity in society and that makes use of the potential of the population's collective skills. Our vision is Knowledge for a better world and our values are creative, critical, constructive and respectful. We believe that an organization that is equal, diverse and gender-balanced is essential for us to achieve our goals.

We strive to attract employees with different skills, life experiences and perspectives to contribute to even better problem solving of our societal mission in research and education.

At NTNU we want to increase the proportion of women in scientific positions. We have a number of measures to promote equality.

Salary and conditions

In the position of PhD Candidate, code 1017, your gross salary will normally be NOK 580 000,-per annum depending on qualifications and seniority. A 2% statutory contribution to the State Pension Fund is deducted from the salary.

The employment period is 3 years.

For employment as a PhD Candidate, it is a prerequisite that you gain admission to the PhD programme in Engineering within three months of your employment contract start date, and that you participate in an organised doctoral programme throughout the period of employment.

As an employee at NTNU, it is important that you keep yourself up to date with academic and organisational changes and adapt to them.

For the necessary professional and social interaction, it is a prerequisite that you are physically present and available to the institution on a daily basis.

The appointment is carried out in accordance with the principles of the State Employees Act, and Export control (legislation that regulates the export of knowledge, technology and services). Candidates who, after assessment of the application and attachments, are considered to bein conflict