SHORT DESCRIPTION

Research on computational thermodynamics and kinetics of metallic alloys. CalPhaD-based calculations, predicting microstructural features, will be used to efficiently explore alloy compositions and process parameters. The generated data will be used to optimize alloys and processes and to train machine learning algorithms. This is part of a large-scale collaborative project focused on leveraging artificial intelligence for the sustainable design of efficient alloys and processes, and will thus require close teamwork with several academic and industrial partners.


OTHER DETAILS

Ref. num. 2024-DT-R1-125

Pre-doctoral research in computational thermodynamics and kinetics for metallic alloy design and process optimization

In Evaluation. It is not possible to apply anymore


IMDEA Materials Institute is a public research organization founded in 2007 by Madrid’s regional government to carry out research of excellence in Material Science and Engineering by attracting talent from all over the world to work in an international and multidisciplinary environment. IMDEA Materials has grown rapidly since its foundation and currently includes more than 120 researchers from 22 nationalities and has become one of the leading research centers in materials in Europe which has received the María de Maeztu seal of excellence from the Spanish government. The research activities have been focused on the areas of materials for transport, energy, and health care and the Institute has state-of-the-art facilities for processing, characterization and simulation of advanced materials.

More information can be found at our webpage.


Description

IMDEA Materials Institute has an immediate opening for a predoctoral position on the topic of “Computational thermodynamics and kinetics for alloy design and process optimization”.

This is part of a large-scale collaborative project focused on leveraging artificial intelligence for the sustainable design of efficient alloys and processes. The overall objective of the project is to develop innovative digital methods for smart design, processing, and characterization of sustainable metallic materials with improved properties. The focus will be on several “near-net shape” fabrication (e.g. 3D printing) methods of steels. The project involves a national consortium of several (12) partners, including universities, research centres, and industries, with whom close collaborations are expected.

Within the scope of this collaborative project, the research project will focus on using state-of-the-art computational thermodynamics (e.g. CalPhaD) and kinetics (e.g. mean-field theories) in order to screen a broad range of alloy compositions and process parameters to predict resulting microstructures. These simulations, linking processing to microstructures, will be used to train artificial intelligence algorithms, and to feed in other models (e.g. simulations linking microstructures to properties). Simulations will be calibrated using experimental data generated by partners within the scope of the project.

Concretely, the project will rely on using and developing computational models for microstructure formation and evolution, to be used for high-throughput exploration of alloy compositions and processing parameters. From the fundamental aspect, one important topic will relate to the consideration of parameter uncertainties, their propagation, and their effect on resulting microstructure (and hence properties).

The student will learn essential concepts of alloy design, metallurgy, advanced manufacturing (e.g. 3D printing) of steels, as well as advanced skills and hands-on expertise on scientific programming, computational thermodynamics (CalPhaD), and modelling of phase transformations. Whereas close collaborations with experimentalists are expected within the project, this specific project will focus primarily on the development of computer simulations. Therefore, relevant candidates are expected to have background skills and interest in scientific programming, computational modelling, and/or mathematics applied to engineering problems.


Requirements
  • Master’s degree in mechanical engineering, metallurgical engineering, industrial engineering, materials science, materials physics, chemistry, chemical engineering, or equivalent.
  • Experience or interest in the following field will be positively evaluated: computational modelling of materials (e.g. thermodynamics and kinetics), scientific programming, applied mathematics for engineering.
  • Scientific curiosity and attention to details.
  • English (written and oral) proficiency.

Conditions
  • Full time employment and enrolment in a relevant doctoral programme.
  • Position available immediately and open until filled.

Applications are processed upon reception. The position might be closed once ten working days have passed since publication, so we encourage early application.

The working language of the Institute is English. Full command of the English language is required in all positions.

WHAT YOU WILL FIND AT IMDEA:

Stimulating environment where you can grow professionally.

IMDEA Materials Institute is committed to equal opportunities, diversity and the promotion of a healthy work environment and work-life balance. Female applicants are encouraged to apply to our research and technical positions. See our Gender Equality Plan here and our Code of Ethics here.

Besides on-the-job technical training, IMDEA Materials Institute is committed to training the Institute’s scientists and staff in “soft” or transversal skills. See the available training here.

Meet some of our alumni to see what it is like to work with us.