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Experimental PhD Position Corrosion Detection and Lifetime Prediction with AI

TU Delft Delft (21 km)
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36 - 40 uur

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TU Delft
Experimental PhD Position Corrosion Detection and Lifetime Prediction with AI
Gesloten
TU Delft Delft (21 km)
3.059 tot 3.881
36 - 40 uur
Status Gesloten
Er kan niet meer worden gesolliciteerd

Wat wij vragen

Opleiding
MSc degree in Materials Science, Metallurgy, Mechanical Engineering, Chemical Engineering or a related field.
Ervaring
Proficiency with Data Science techniques. Excellent analytical skills, initiative, inventiveness, curiosity, diligence, and critical thinking. Ability to work with scientific and industrial partners. Strong communication skills (high English proficiency), team player, and good social behaviour. Creative, open-minded, and proactive researcher. Excellent experimental, analytical, and problem-solving skills. Self-driven attitude, creativity and autonomy.
Talen
  • Je beheerst Engels

Wat wij bieden

Salaris
€ 3.059 tot € 3.881
Uren
36 tot 40 uur per week
Dienstverband
fulltime
Type vacature
intern

Vacaturebeschrijving

Experimental PhD Position Corrosion Detection and Lifetime Prediction with AI

Would you love to apply Data Science to Military Corrosion Technology? Join us on our journey to ensure Safe Operation of Military Systems.

Job description

Join the Corrosion Technology and Electrochemistry (CTE) group, part of the Department of Materials Science and Engineering at the Faculty of Mechanical Engineering, in close collaboration with the Netherlands Defence Academy. The CTE group is a dynamic team of researchers, including PhD candidates, postdocs, and faculty members. Our group focuses on understanding and mitigating corrosion processes, and on the development of electrocatalysts and electrochemical sensors through the synthesis of materials and the use of advanced electrochemical methods and surface analysis techniques. We aim to deepen the fundamental knowledge of electrochemistry and surface science and translate this into practical, sustainable solutions for energy and materials applications.

Increasingly strict performance requirements for components lead to new material combinations and potential corrosion problems. The most dangerous of these are highly localized. Localized corrosion under a coating is however typically difficult to detect visually. Electrochemical Noise (EN) can detect this at an early stage and is not limited by geometric characteristics. Moreover, EN measures passively and continuously, making it very suitable for permanent monitoring or as an accelerated testing method. The effectiveness of EN depends on effective data analysis. Until now, specific EN fingerprints of localized corrosion are determined manually. This is a tedious procedure that requires considerable expert knowledge. Artificial intelligence or machine learning (AI/ML) models can offer a solution here.

This project aims to determine to what extent AI/ML models based on electrochemical sensor data are able to identify and quantify local forms of corrosion. We are looking for a skilled PhD researcher to investigate these models, together with the Netherlands Defence Academy. Your work as a PhD researcher involves the following:

  • Determining the required discrimination ability for classification and quantification of corrosion phenomena, e.g. Differences and similarities in data between crevice- and different forms of pitting corrosion.
  • Investigating which types of AI/ML models can meet these requirements.
  • (Further) developing suitable AI/ML models.
  • Investigating which requirements the training data for the AI/ML models must meet, including type, quantity, and number of corrosion classes.
  • Performing laboratory experiments to validate the corrosion classification and -quantification for representative forms of corrosion that typically cause problems in military systems.
  • Further validation on field data from actual military systems.
Job requirements

Job requirements:

  • MSc degree in Materials Science, Metallurgy, Mechanical Engineering, Chemical Engineering or a related field.
  • Proficiency with Data Science techniques.
  • Excellent analytical skills, initiative, inventiveness, curiosity, diligence, and critical thinking.
  • Ability to work with scientific and industrial partners.
  • Strong communication skills (high English proficiency), team player, and good social behaviour.

The following will make you stand out:

  • Creative, open?'minded, and proactive researcher.
  • Excellent experimental, analytical, and problem?'solving skills.
  • Self?'driven attitude, creativity and autonomy.

Important note: due to the specific nature of the subject, this vacancy is only applicable for Dutch and/or EU/NATO nationalities. The candidate will be subjected to a defence safety screening procedure.

TU Delft (Delft University of Technology)

Delft University of Technology is built on strong foundations. As creators of the world?'famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem?'solvers, both in business and in a social context.

At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

Challenge. Change. Impact!

Faculty Mechanical Engineering

From chip to ship. From machine to human being. From idea to solution. Driven by a deep?'rooted desire to understand our environment and discover its underlying mechanisms, research and education at the ME faculty focusses on fundamental understanding, design, production including application and product improvement, materials, processes and (mechanical) systems.

ME is a dynamic and innovative faculty with high?'tech lab facilities and international reach. It's a large faculty but also versatile, so we can often make unique connections by combining different disciplines. This is reflected in ME's outstanding, state?'of?'the?'art education, which trains students to become responsible and socially engaged engineers and scientists. We translate our knowledge and insights into solutions to societal issues, contributing to a sustainable society and to the development of prosperity and well?'being. That is what unites us in pioneering research, inspiring education and (inter)national cooperation.

to go to the website of the Faculty of Mechanical Engineering. Do you want to experience working at our faculty? These videos will introduce you to some of our researchers and their work.

Conditions of employment

Doctoral candidates will be offered a 4?'year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.

As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline?'related and research skills.

, offers information on their website to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands.

) and/or Prof. Dr. Arjan Mol ().

Application procedure
  • Your detailed CV.
  • Your cover (motivation) letter, two references and the abstract of your MSc thesis in English.

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English?'taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements.

Please note:

  • You can apply online. We will not process applications sent by email and/or post.
  • knowledge security.
  • Please do not contact us for unsolicited services.
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