Postdoc in Machine Learning-driven Modeling of Metallic Microstructures

Updated: 4 months ago
Deadline: 07 Jan 2024

17 Nov 2023
Job Information
Organisation/Company

Delft University of Technology (TU Delft)
Research Field

Technology
Researcher Profile

Recognised Researcher (R2)
Country

Netherlands
Application Deadline

7 Jan 2024 - 22:59 (UTC)
Type of Contract

Temporary
Job Status

Not Applicable
Hours Per Week

40.0
Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme
Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

The challenge:
Contribute to cutting-edge research in the field of materials science by developing innovative machine learning-driven models for the analysis and prediction of complex metallic microstructures. This role presents a unique opportunity to address critical questions related to the structure-property relationships of metals, unlocking new possibilities for engineering and design in various industries.

Our vision:
By developing advanced data-driven models and analytical tools, we aim to enhance our understanding of how thermomechanical processing parameters influence the microstructural features and in turn, the mechanical properties of metallic materials. Through this, we hope to accelerate the development of next-generation materials with improved performance, impacting a wide range of applications.

Why join us?

  • Lead a pioneering project at the forefront of machine learning and materials science.
  • Work with international collaborators from diverse disciplines.
  • Access state-of-the-art resources and computational facilities.
  • Supervise PhD and MSc researchers.
  • Receive mentorship and support in developing your academic career.

This will be a 3-year Postdoc position embedded in the research group of Dr. Sid Kumar (https://www.mech-mat.com/ ).


Requirements
Specific Requirements

Why join us?

  • A Ph.D. in a relevant field (e.g., materials science, mechanical engineering, applied mechanics).
  • Experienced in machine learning for scientific applications.
  • Strong programming skills (Python, PyTorch, TensorFlow, etc.).
  • A passion for cutting-edge research and the drive to solve complex problems.
  • Excellent communication and teamwork abilities.

Additional Information
Benefits

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.


Selection process

Are you interested in this vacancy? Please apply before 7 January 2024 via the application button and please enclose:

  • A detailed curriculum vitae (CV) including the current status of your PhD and a list of publications and projects
  • Self-selected best scientific paper (journal or conference) relevant to this position
  • List of 2-3 references
  • A cover letter with your motivation for joining this position

Notes:

  • We encourage applicants to apply right away and do 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.

Additional comments

For more information about this vacancy, please contact Dr. Sid Kumar ([email protected] )


Website for additional job details

https://www.academictransfer.com/334703/

Work Location(s)
Number of offers available
1
Company/Institute
Delft University of Technology
Country
Netherlands
City
Delft
Postal Code
2628 CD
Street
Mekelweg 2

Where to apply
Website

https://www.academictransfer.com/en/334703/postdoc-in-machine-learning-driven-m…

Contact
City

Delft
Website

http://www.tudelft.nl/
Street

Mekelweg 2
Postal Code

2628 CD

STATUS: EXPIRED

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