Phd position ai-driven generative engineering design from qualitative and quantitative requirements

PhD Position AI-Driven Generative Engineering Design from Qualitative and Quantitative Requirements

Excited by Artificial Intelligence and Engineering Design? Join us and develop foundational methods that will transform how data and creativity are used to solve complex problems.

Job description

We are seeking future trailblazers with motivation to transform the design process with Artificial Intelligence. At a high level, engineering design involves mapping a problem's functional requirements to the physical parameters which define a solution. In the case of quantitative design objectives, processes like topology optimization can be utilized to converge on parameters which maximize performance. However, real-world requirements relating to societal, sustainable, and manufacturing needs are not necessarily easily quantified. Considering both qualitative and quantitative functional information together for design optimization is a complex challenge.

This position is an opportunity to connect recent advancements in AI such as language modeling and computer vision with fundamental Mechanical Engineering techniques such as topology optimization. This research involves the development of methods and tools to represent complex functional requirements and geometric form for generative design. The envisioned output of this project is a design representation model capable of encoding qualitative and quantitative design requirements together in a unified latent "semantic" space which can be used to generate geometrically optimized physical components. Success in this endeavor will mean a transformation of how multimodal data is utilized to maximize design performance and sustainability.

Job requirements

We seek evidence of the following qualifications in candidates' application materials:

• MSc Degree in Mechanical Engineering, Computer Science, or related fields.

• Programming skills in Python or MATLAB.

• Engineering design experience.

• Motivation for pursuing original contributions to science at the doctoral level.

• Ability to identify meaningful research problems, communicate technical information clearly and concisely, and lead organized and collaborative progression following the scientific method.

Further distinguishing relevant competencies:

• Experience with training and validation of Machine Learning (ML) models.

• Experience with dataset construction and curation.

• Experience using ML libraries such as Tensorflow, Pytorch, Hugging Face Transformers.

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

• Duration of contract is 4 years Temporary
• A salary based on Promovendus of the CAO for Dutch Universities with a salary between €2901 - €3707 gross per month based on a fulltime contract (38 hours), plus 8% holiday allowance and an end-of-year bonus of 8.3%.
• An excellent pension scheme via the ABP.
• The possibility to compile an individual employment package every year.
• Discount with health insurers on supplemental packages.
• Flexible working week.
• Every year, 232 leave hours (at 38 hours). You can also sell or buy additional leave hours via the individual choice budget.
• Plenty of opportunities for education, training and courses.
• Partially paid parental leave.
• Attention for working healthy and energetically with the vitality program.

Additional information

Are you interested in this vacancy? Please apply no later than 2 March 2025 via the application button and upload the following documents:

1. Cover letter stating your motivation (maximum 1 page).

2. Past project description: Using maximum 1 page, share a project you worked on. Feel free to be creative in how you communicate; the only guideline is the 1-page constraint.

3. Detailed curriculum vitae (CV).

4. Transcript (document from your institution listing BSc and MSc courses with grades).

5. Names of three persons and their email addresses who could be contacted for a reference.

Please note:

• Note that the selection committee is seeking specific and concise evidence of your motivation to pursue a PhD in your submissions. Generic letters generated by a language model will not be considered.
• A pre-employment screening can be part of the selection procedure.
• For the final candidates, a knowledge security check will be part of the application procedure. For more information on this check, please consult Chapter 8 of the . We carry out this check on the basis of legitimate interest.
• here for more information.
• Please do not contact us for unsolicited services.