Postdoc Composite Design and Manufacturing Using Applied Machine Learning Methods

Postdoc Composite Design and Manufacturing Using Applied Machine Learning Methods

Published Deadline Location
1 Feb 3 Mar Delft
Explore and develop scalable machine learning methods for aerospace structures' design and manufacturing

Job description

This postdoctoral research aims at exploring statistical methods that enable the data-driven analysis and design of aerospace composite structures. The candidate should have a background in Statistics, Uncertainty Quantification, Deep Learning or Bayesian machine learning methods, and is motivated to apply these methods to solve Engineering problems. The candidate will be working in the CAELESTIS project including a team of experimentalists; therefore, interaction with these colleagues is expected. The research group hosting this candidate includes experts in simulation and machine learning methods, but it is currently lacking proficiency in Statistics and uncertainty quantification. The postdoc will be rewarded with significant independence, and is expected to help supervise one PhD student working on the topic. Additional details can be provided during the interview. There is some flexibility concerning the type of methods to explore, depending on the interests and expertise of the candidate (within reasonable bounds!).

CAELESTIS main objective is to enable the EU aircraft industry to design and manufacture disruptive aircraft structures and engines with enhanced prediction capacities (product performance and manufacturability), to widen the design space and reduce the uncertainties potentially encountered along the product and engineering lifecycle, which are currently limiting their introduction into service.

Specifications

Delft University of Technology (TU Delft)

Requirements

Applicants must have the following qualifications:

  • Strong computational skills.
  • Strong background in mechanical/aerospace/civil engineering, materials science, physics.
  • Background in statistics or related field is a plus.
  • Proficiency with machine learning methods and corresponding software packages.
  • An interest in applying these methods to modeling mechanics and/or manufacturing of composites (past experience is a plus, but not required).
  • The ability to work well in a collaborative setting.

Conditions of employment

Fixed-term contract: 2 years.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities (based on scale 10: €3,226.00 - €5,090.00). The contract of employment is offered for two years. The position is open for 36-40 hours per week. The TU Delft offers a customisable compensation package, a discount on health insurance and sport memberships, 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.

Employer

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!

Department

Faculty Aerospace Engineering

The Faculty of Aerospace Engineering at Delft University of Technology is one of the world’s most highly ranked (and most comprehensive) research, education and innovation communities devoted entirely to aerospace engineering. More than 200 science staff, around 270 PhD candidates and close to 3000 BSc and MSc students apply aerospace engineering disciplines to address the global societal challenges that threaten us today, climate change without doubt being the most important. Our focal subjects: sustainable aerospace, big data and artificial intelligence, bio-inspired engineering and smart instruments and systems. Working at the faculty means working together. With partners in other faculties, knowledge institutes, governments and industry, both aerospace and non-aerospace. Working in field labs and innovation hubs on our university campus and beyond. 

Click here to go to the website of the Faculty of Aerospace Engineering.

Additional information

For more information about this vacancy, please contact Dr. Baris Caglar, Assistant Professor at Faculty of Aerospace Engineering (co-supervising candidate in person), email: B.Caglar@tudelft.nl or Dr. Miguel Bessa, Associate Professor at Brown University (co-supervising candidate remotely), email: miguel_bessa@brown.edu. Temporary stays at Brown University with the Bessa group are possible, in case the candidate is interested.

For more information about the application procedure, please contact recruitment-lr@tudelft.nl.

Specifications

  • Postdoc
  • Engineering
  • 36—40 hours per week
  • €3226—€5090 per month
  • Doctorate
  • TUD04334

Employer

Delft University of Technology (TU Delft)

Learn more about this employer

Location

Mekelweg 2, 2628 CD, Delft

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Application procedure

Are you interested in this vacancy? Please apply no later than 3 March 2024 via the application button. Applicants are invited to submit:

  • A letter of motivation.
  • A detailed CV including publication list.
  • Summary of academic record or research experience.
  • Names of three references.

Please note:

  • Applications will be periodically reviewed also before the application deadline. Candidates are encouraged to submit their application as soon as they are ready and not wait until the deadline.
  • A pre-employment screening can be part of the selection procedure.
  • You can apply online. We will not process applications sent by email and/or post.
  • Please do not contact us for unsolicited services.

Application procedure

Application procedure

Are you interested in this vacancy? Please apply no later than 3 March 2024 via the application button. Applicants are invited to submit:

  • A letter of motivation.
  • A detailed CV including publication list.
  • Summary of academic record or research experience.
  • Names of three references.

Please note:

  • Applications will be periodically reviewed also before the application deadline. Candidates are encouraged to submit their application as soon as they are ready and not wait until the deadline.
  • A pre-employment screening can be part of the selection procedure.
  • You can apply online. We will not process applications sent by email and/or post.
  • Please do not contact us for unsolicited services.

Make sure to apply no later than 3 Mar 2024 23:59 (Europe/Amsterdam).