PhD Candidate in Deep Learning Enhanced FSI analysis of Modular Floating Structures

Norges teknisk-naturvitenskapelige universitet (NTNU); Trondheim; On-site; NOK 496,000 - 606,000; Full time

Benefits offered by this job

Open and inclusive working environment

Pension fund (SPK)

Job summary

NTNU seeks a PhD Candidate in Deep Learning enhanced FSI modelling of Multi-modular Floating Structures. The project sits in AIMOS, advancing AI methods for offshore structures and digital twins. You will work with high-fidelity CFD-FEA data to develop physics-informed surrogates and predictive models.

The role involves coupling CFD–FEM, developing data-driven predictions, and collaborating with peers. Strong English and a solid master’s background are required, with admission to NTNU’s PhD

Qualifications

• Master's degree with 120 credits at master's level as required.
• Strong academic record with grade equal to B or better on NTNU scale.
• Eligibility for admission to the faculty's doctoral program.

Responsibilities

• Take courses totaling at least 30 ECTS.
• Run coupled CFD–FEM simulations for waves, mooring, and deformation.
• Develop deep learning surrogate models for fast predictions.
• Validate models with simulations, experiments and field data.
• Analyze dynamic behavior of modular floating structures under varying sea states.
• Collaborate with AIMOS colleagues in intelligent control and smart materials.
• Publish in high-quality journals and present at conferences.

Skills

Python

MATLAB

English proficiency

Education

Master's degree in marine technology, civil engineering, mechanical engineering, applied mathematics or equivalent

Tools

STAR-CCM-ABAQUS

PyTorch

TensorFlow

CFD/FEM software

Job description

About The Position

Would you like to work at the intersection of artificial intelligence and offshore engineering, contributing to the next generation of intelligent floating structures? The Department of Marine Technology at NTNU has a vacancy for a PhD Candidate in Deep Learning enhanced FSI modelling of Multi-modular Floating Structures. 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. Multi-modular floating structures are emerging as a promising solution for scalable offshore applications where conventional fixed-bottom systems are impractical. These systems consist of multiple interconnected modules subjected to waves, current, and mooring loads, resulting in highly nonlinear coupled hydrodynamic and structural behaviors. High-fidelity CFD-FEA based FSI simulations provide valuable insight but remain computationally expensive for large design spaces, long-duration simulations, and real-time applications. This PhD project will develop physics-informed deep learning and surrogate modelling approaches to accelerate simulation, uncertainty quantification, structural response prediction, and digital twin capabilities using data generated from high fidelity CFD-FEA simulations, experiments and field measurements. The position offers the opportunity to work on cutting-edge research with strong relevance to offshore renewable energy and 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.
• Conduct coupled CFD–FEM (e.g. STARCCM-ABAQUS) simulation of wave-induced motions, connector loads, mooring loads and structural deformation. This may be extended to include potential flow theory based modelling as well.
• Develop deep learning surrogate models for fast prediction of motions, stresses, and loads
• Validate the deep learning model using numerical simulations, experiments data, and field measurements.
• Analyse the dynamic behavior of modular floating structures, including connector loads, load redistribution, resonance effects, inter-module coupling, and response under varying sea states.
• Collaborate with other PhD candidates in AIMOS project, working with intelligent control and smart materials.
• Write scientific articles in high quality journals and present results in conferences

Be prepared for changes to your work duties after employment.

Required Selection Criteria

• You must have a relevant master’s degree in marine technology, civil engineering, mechanical engineering, applied mathematics or equivalent. Your course of study must correspond to a five-year Norwegian course, where 120 credits have been obtained at master's level.
• 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.

PLEASE NOTE: For detailed information about what the application must contain, see paragraph “About the application”.

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 marine, offshore, or structural engineering disciplines, including structural mechanics, hydrodynamics and machine learning
• Strong programming skills in Python and/or MATLAB
• Experience with scientific computing, CFD/FEM software, potential flow theory or machine learning frameworks (e.g., PyTorch, TensorFlow).
• Strong written and oral communication skills in English.

Personal characteristics

To complete a doctoral degree (PhD), it is important that you are able to:

• Highly motivated and interest-driven to explore complex scientific and engineering problems
• Work independently and in structured way, as well as collaboratively within an interdisciplinary team.
• Communicate effectively and 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
• 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
• 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.

If you think this position is relevant and interesting, we encourage you to apply, regardless of gender, functional ability and cultural background, or whether you have been out of work for a period of time.

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 550 800,- 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 the doctoral work in addition to 4 months/year of teaching assistance.

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 organized 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 organizational 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 be in conflict with the criteria in the latter act, will not be able to be employed.

About The Application

The attachments (including a description of your scientific work) must accompany the application as these documents form the basis of the application assessment. The documents must be in Norwegian/a Scandinavian language or English.

Please note: the application will only be assessed on the basis of the information we have received by the application deadline. Therefore, make sure that your application clearly shows how your skills and experience meet the criteria described above. The application and all attachments must be sent electronically via Jobbnorge.no. If you are invited to an interview, you must bring certified copies of certificates and diplomas upon request.

The Application Must Include

• Transcripts and diplomas for Bachelor's and Master's degrees
• CV
• Copy of Master's thesis. If you have recently submitted your Master's thesis, you can attach a draft of the thesis. Documentation of a completed Master's degree must be presented before taking up the position.
• Project outline containing proposals for an overall description of research questions, theoretical perspectives, methodological design for the project and progress plan (maximum 1500 words/4 pages)
• Short letter of motivation (400 words/1 page)
• Possibly publications etc. other relevant research work
• Names and contact information of three relevant referees

If all, or parts, of your education has been taken abroad, we also ask you to attach documentation of the scope and quality of your entire education, both Bachelor's and Master's education, in addition to other higher education. If your institution uses “diploma supplement” (normal for most European institutions), you must attach this. A description of the documentation required can also be found here. If you already have a statement from Norwegian Directorate for Higher Education and Skills (HK-dir), please attach this as well.

Joint work will be considered. If it is difficult to identify your contribution to joint work, you must attach a brief description of your participation.

When assessing the best qualified, we emphasize necessary qualifications such as education, experience and personal suitability. Motivation for the position, ambitions, and potential for research will also count when assessing the candidates.

NTNU recognizes a wide range of academic contributions and has committed itself to The San Francisco Declaration on Research Assessment and CoARA (responsible assessment of a greater breadth of academic contributions in accordance with NTNU's social mission).

General information

A public list of applicants with name, age, job title and municipality of residence is prepared after the application deadline. If you wish to be exempt from entry on the public applicant list, this must be justified. Assessment will be made in accordance with current legislation. You will be notified if the exemption is not granted.

If you think this position looks interesting and in line with your qualifications, you are welcome to apply.

If you have any questions about the position, please contact Associate Professor Zhaolong Yu, telephone [phone], email [e-mail]. If you have any questions about the recruitment process, please contact Maria Hjertner, [e-mail]

Application deadline: 25.09.2026

For practical information about working at NTNU, please visit this webpage.

The city of Trondheim

is a modern European city with a rich cultural scene. Trondheim is the tech capital of Norway with a population of 200,000. The Norwegian welfare state, including healthcare, schools, kindergartens and overall equality, is probably the best of its kind in the world. Professional subsidized day-care for children is easily available. Furthermore, Trondheim offers great opportunities for education (including international schools) and possibilities to enjoy nature, culture and family life and has low crime rates and clean air quality.

NTNU - knowledge for a better world

The Norwegian University of Science and Technology (NTNU) creates knowledge for a better world and solutions that can change everyday life.

Department of Marine Technology

We develop methods and technology related to the blue economy: oil and gas extraction at sea, ship technology and the equipment industry, fisheries and aquaculture. We also have a strong commitment to the development of sustainable solutions for offshore renewable energy, coastal infrastructure, and marine robotics. Marine technology helps to solve major global challenges related to the environment, climate, energy, food and efficient transport. The Department of Marine Technology is one of eight departments in the Faculty of Engineering.