20 beste vacatures voor de functie van machine learning in delft, zh (nieuwe medewerkers gezocht)

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Graduation Internship | Damage localization of a vessel using iFEM and deep learning

TNO -
Delft

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Vacaturegegevens

Parttime | Fulltime
€ 615 per maand
2 dagen geleden

Secundaire arbeidsvoorwaarden

Reiskostenvergoeding
Bedrijfslaptop

Kwalificaties

Werktuigbouwkunde
Civiele techniek
Microsoft Excel
Lucht- & ruimtevaarttechniek
Master
Bachelor
MBO
Civiele techniek
Python

Volledige vacaturetekst

About this position

Structural Health Monitoring (SHM) is a continuous process of damage identification strategies and can be used for condition monitoring of a navy vessel. Knowing the structural condition of a navy vessel is important to maximize the operability of the vessel. For vessels, damage prognostics after an extreme event like a blast is even important but significantly more complex. Recently Inverse FEM combined with AI techniques has emerged as a potential technology to help with this and be able to identify, localize and assess the damage after any extreme military threat. Inverse Finite Element Method (iFEM) is a shape and stress-sensing technique to reconstruct the displacement field using a limited number of sensors. To apply this approach, iFEM combined with an AI model needs to be developed, trained and validated. This work will be done in collaboration with and under the guidance of TNO Naval and Offshore Structure Department. There is also the possibility of combining this with an internship.

What will be your role?

During this graduation internship, you will investigate and develop how structural damage can be localized after an extreme accidental load. You will develop iFEM tooling to reconstruct displacement and stress/strain fields for loading condition and geometry. Developing and validating a Deep Neural Network or other machine learning method to identify the damage locations. You will combine literature research with calculations and numerical analyses, using tools such as Python and finite element software.

Your task will include:

Implemented iFEM tool for navy applications be able to reconstruct displacement and stress/strain fields for a loading condition for a given geometry.
Developing Deep Neural Network (DNN) or another machine learning method to identify the damage location.
Validating the developed tooling.
Potentially, identify the limitations of iFEM for SHM considering noise.
Potentially, developing tool to assess remain strength.

Through your work, you will contribute to a larger development of investigating how monitoring implemented can improve operations, support long-term ambition of decision-making SHM for Maritime and offshore structures. You will learn how to implement and improve state-of-the-art technology for maritime and offshore applications and how to adopt technology from other fields into the maritime domain.

What we expect from you

We are looking for a student with a background in maritime engineering, mechanical engineering, civil engineering, aerospace engineering or a similar technical degree. You have an interest in ship structures, numerical simulations and artificial intelligence. You are curious and able to work independently within a multidisciplinary environment.

Desired experience:

Experience with finite element modelling (e.g. Abaqus, Ansys or similar software).
Experience or knowledge in developing and validating ML techniques.
Knowledge of strength of materials, structural mechanics and dynamics.
Basic programming skills (Python).
You are in the final stage of your degree in civil engineering, marine engineering or aerospace engineering (or a similar degree).

What you'll get in return

An internship at TNO means working in an environment where substance and impact are central. You will become part of a knowledge organisation where research and practice come together, and where experts collaborate on solutions to current societal and technological challenges.

Your internship is a period in which you can discover what suits you, where your strengths lie and what you would like to learn next. You are part of a professional working environment, gain insight into how things work in practice, and have the opportunity to build experience that goes beyond this internship alone. For many students, an internship is therefore also a first step in discovering whether TNO could be a potential next step after graduation.

In addition, we offer you:

A professional and innovative internship environment in which you actively contribute to societal and technological challenges, working alongside leading experts in your field.
Personal and dedicated supervision, with focus on your learning objectives, development and study assignment.
Room to develop: you gain relevant work experience, develop both your subject‑specific and professional skills, and build a valuable network.
Use of a laptop and the facilities you need to perform your work effectively.
A monthly internship allowance of € 615 for a full-time internship, for MSc, BSc and vocational education (MBO) students.
Up to eight hours of leave per internship month for a full-time internship, allowing you to balance your internship with your studies and personal life.
A contribution towards travel expenses if you are not entitled to a student travel card.
A free membership to Jong TNO: the network for young colleagues, where you can meet other TNO colleagues and participate in sports activities, professional and personal development activities, and social events such as the annual ski trip.

TNO as an employer

Our people are at the heart of TNO. Their curiosity, expertise and entrepreneurial mindset make it possible to deliver high-impact research and innovations that contribute to society’s sustainable wellbeing and prosperity. That is why we invest in an inspiring and inclusive working environment where colleagues can excel, have autonomy and continue to grow.

Your talent and ambition have every opportunity to flourish at TNO. You work with experts (both within and beyond TNO), have access to advanced technology and the freedom to explore, experiment and innovate. Our strength lies in independence, reliability and collaboration. We find each other in wonder and ingenuity. We are driven to push boundaries. By working with businesses and government, and by connecting different perspectives, we strengthen our innovative capability and create responsible, meaningful results.

At TNO, we believe this is our time to help society, government and business move forward faster. Together with driven colleagues, you turn knowledge into concrete innovations or ventures that truly make a difference by combining the power of science and entrepreneurship. And in doing so, you make your mark on our time.

Has this job opening sparked your interest?

Then we’d like to hear from you! Please contact us for more information about the job or the selection process. To apply, please upload your CV and covering letter using the ‘

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Verfijn je zoekopdracht

machine learning vacatures in delft, zh

Graduation Internship | Damage localization of a vessel using iFEM and deep learning

2027 | EMEA | The Hague | Engineering | Seasonal/Off Cycle Internship

Internship- Mechanical Design & Integration

Senior Petrophysicist and Rock Physicist

Senior machine learning engineer

Machine Learning-ai Engineer

PhD in Computational Imaging for High-Throughput Applications (1.0 fte)

Software Developer (VBA developer with Python skills)

Postdoc on Causal Machine Learning for Spatio-temporal Datasets

Senior Quantum Algorithm Expert

Application Engineer/ Administrator

Internship: Research into a Compact Cutter Bar Drive for the Lely Exos

Conversational Designer (Sr.)

IT Support Analyst

AI Engineer / Python Developer

Data scientist

Automation Test Analyst

Scientific Programmer / Post-Doctoral Researcher on Project Hippocampus: The Future of OpenML

Master Data Specialist

Internship: Sensor Data Fusion and Machine Learning for Human Activity Detection

Ik wil de nieuwste vacature-alerts ontvangen voor de functie van machine learning in delft, zh

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