Researcher in modeling for material design

Tasks

At the Hultgren Laboratory at the Department of Materials Science, we are looking for a researcher with a strong interest in developing and applying machine learning methods for material design, particularly steel design. The position is part of our growing research environment focusing on physics-informed AI tools for material design and characterization.

In a collaborative project with industrial partners, you will work on developing physics-informed models for the heat treatment of steel. A central part of the physics-informed approach is to use thermodynamically based understanding, a long-standing core competence at KTH, to guide model development and ensure physically consistent predictions. You will contribute to models that link composition, processing, microstructure, and properties, and support the development of new alloys and processes for critical industrial challenges such as electrification and circular production flows based on recycled material.

Experimental input data and validation will also be an important part of the work. You will have the opportunity to develop an understanding of experimental methods and their limitations, in close collaboration with experimental experts at the Hultgren Laboratory.

The position is well suited for candidates with a background in computational materials science and materials engineering or related areas, who want to deepen their expertise in physics-informed machine learning for material design and work closely with industry and leading academic actors in steel research. You will have excellent opportunities to contribute to the development of next-generation digital tools for sustainable steel design.

Qualifications

Requirements

• A completed doctoral degree or equivalent foreign degree in computational materials science and materials engineering or a related field.
• Research experience in machine learning within materials science, demonstrated through journal publications and international conference presentations.
• Good programming skills with, e.g., Python.
• Very good ability to express yourself in English, both orally and in writing, as required in daily work.
• You are self-driven, motivated, and have the ability to take initiative and drive projects.
• Ability to collaborate and experience working in interdisciplinary environments.
• Awareness of diversity and equal treatment issues, with a particular focus on gender equality.
• Ability to communicate research and development work clearly.

Meritorious

• A doctoral degree or equivalent foreign degree obtained within the last three years before the application deadline.
• Experience in method development that integrates physics-based approaches, data-driven methods, and experiments.
• Potential and interest to develop into a leader in machine learning for material design and characterization in a primarily experimental research environment.

We will place great emphasis on personal qualities.

Become part of KTH

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Read more about our benefits and what it is like to work and develop at KTH.

Union representatives

Contact details for union representatives.

Application

You apply via KTH's recruitment system. As an applicant, you are primarily responsible for ensuring that your application is complete when submitted.

The application should include:

• CV including relevant professional experience and knowledge.
• Copy of degree certificates and transcripts from your previous university studies. Translations into English or Swedish if the original documents are not issued in either of these languages.
• A brief account of why you want to conduct research, your academic interests, and how they relate to your previous studies and future goals. Max 2 pages long.

The application must reach KTH no later than the last application date at midnight, CET/CEST (Central European Time/Central European Summer Time).

About the position

The employment is for a fixed term according to agreement - for up to 12 months, with commencement by agreement.

Other

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