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

Ntnu; Trondheim; Hybrid; NOK 496,000 - 606,000; Full time

Job summary

NTNU's Department of Marine Technology invites applications for a PhD Candidate position focused on deep learning enhanced FSI analysis of modular floating structures within the AIMOS project. The work combines offshore engineering with AI to accelerate simulations and enable digital twin capabilities.

The candidate will develop physics‑informed DL surrogate models, validate with experiments and field data, and contribute to scientific publications and conferences.

Qualifications

• Master's degree in Marine Technology or related field with a 5‑year Norwegian program.
• Strong academic record with grade B or better on NTNU scale.
• Excellent English (written and spoken).

Responsibilities

• Take courses totaling at least 30 ECTS.
• Conduct coupled CFD–FEM simulations of wave‑induced motions and loads.
• Develop DL surrogate models for fast predictions of motions and stresses.
• Validate DL models with numerical, experimental, and field data.
• Analyze dynamic behavior of modular floating structures and inter‑module effects.
• Publish results and present at conferences; collaborate within AIMOS.

Skills

Python

MATLAB

Machine learning

CFD

FEM

English

Education

Master's degree in Marine Technology

Tools

PyTorch

TensorFlow

STAR-CCM+

ABAQUS

Job description

The Department of Marine Technology has a vacancy for a PhD Candidate in Deep Learning Enhanced FSI analysis of Modular Floating Structures

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

NTNU is a broad-based university with atechnical-scientific profile and a focusin professional education. The university is located in three cities with headquarters in Trondheim.

At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world.

You will find more information about working at NTNU and the application process here.

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 mathematicsorequivalent. 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.
• 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".

• 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 inter‑disciplinary 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
• Open and inclusive working environment with committed colleagues

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 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 is3 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 withinthree 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 andCoARA (responsible assessment of research and recognition 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 have any questions about the position, please contactAssociate Professor Zhaolong Yu, telephone [phone], [e-mail]. If you have any questions about the recruitment process, please contact Maria Hjertner, [e-mail]

NTNU - knowledge for a better world

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.