Delft

Postdoc Artificial Intelligence for the Dynamics of 2D Materials

12.02.2024
  • WO
  • Tijdelijk
Delft University of Technology (TU Delft)

Functieomschrijving

We live in an era where artificial intelligence (AI) stands as a beacon of innovation, where advances in machine learning (ML) profoundly impact many aspects of our society. Nevertheless, the use of ML in engineering is still in its infancy. Many areas of engineering that could leverage on ML include (meta)material characterization and design, computational structural design, and symbolic regression (i.e., obtaining mathematical expressions from experimental data), to name a few. At Delft University of Technology we recognize the immense potential AI holds in revolutionizing a broad range of engineering problems.

In this project we will look at ultra-thin materials, which are at the forefront of technological development due to their extraordinary properties. Graphene, for instance, stands as the strongest, most impermeable, and conductive material known to date. There is a myriad of applications where graphene could find its way. However, the materials’ extreme noise sensitivity gives rise to a plethora of poorly-understood phenomena. Through the use of ML, we will derive precise mathematical expressions that describe the behavior of these materials in the presence of noise, paving the way for unleashing their full potential for extreme sensing in high-tech industries such as aerospace and medical.

As a postdoctoral researcher your tasks will include:

  • Developing on "deep symbolic regression", i.e., an existing ML framework that uses neural networks to determine mathematical expressions from experimental or numerical data.
  • Coordinate the work of related MSc projects.
  • Help with writing proposals to secure further funding for this topic.
  • Publishing in renowned journals, and presenting your research at international meetings.

Functie-eisen

You should have the following qualifications:

  • A strong background in machine learning.
  • Knowledge of Bayesian optimization, Gaussian processes is a plus.
  • Background in mechanics is highly desired.
  • A PhD degree in computer science, applied mathematics, or engineering (mechanical, civil, aerospace, etc.).
  • High motivation for teamwork and excellent communication skills.

Bedrijfsomschrijving

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!

Arbeidsvoorwaarden

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities. The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

For international applicants, TU Delft has the Coming to Delft Service. This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a Dual Career Programme for partners and they organise events to expand your (social) network.

Meer informatie

For more information about this vacancy, please contact Dr. Alejandro M. Aragón, phone: +31 (0)15 278 22 67, e-mail: a.m.aragon@tudelft.nl.