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JobbSafariLediga jobbSenior Materials Informatics Engineer

Senior Materials Informatics Engineer

Ferritico AB

Sammanfattning

Ferritico is seeking a Senior Materials Informatics Engineer for a hybrid full-time position. The role focuses on developing and validating machine learning models for advanced materials, particularly in steel and metallurgy. The engineer will work at the intersection of materials science and computational modeling, translating expertise into practical applications while ensuring models meet industrial engineering needs.
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Jobbet i korthet

Anställningstyp

tillsvidareanstallning

Arbetstid

heltid


Förmåner

Opportunity to influence scientific foundation and product direction in advanced materials development.Work in a collaborative and innovative startup environment.Engagement in the intersection of materials science, AI, and industrial digitalization.

Stockholm

Ansök senast: 2026-07-31
Publicerad: 2026-07-13

Beskrivning

Senior Materials Informatics Engineer

Location: Hybrid

Company: Ferritico

Employment type: Full-time

Ferritico is looking for a Senior Materials Informatics Engineer to develop, validate, and productize physics informed machine learning models for advanced materials, with a strong focus on steel, metallurgy, heat treatment, phase transformations, and process-property relationships.

This is a mid- to senior-level technical role for someone who enjoys working at the intersection of materials science, computational modeling, machine learning, and product development.

About the role

You will contribute to the development of computational and machine learning models for metals and metallurgical applications. The role involves translating materials science expertise into clear model logic, validation workflows, technical requirements, and product features.

You will help ensure that scientific models are technically sound, well-documented, validated, and aligned with real industrial engineering needs.

Key responsibilities

Develop computational and ML-based models for steel metallurgy, heat treatment, transformation temperatures, phase transformations, microstructure evolution, and process-property relationships.

Define model assumptions, expected behavior, validation datasets, limitations, and acceptance criteria.

Improve AI model performance by integrating materials science expertise and physics-informed modeling approaches.

Identify data correlations between process, structure, and properties in steel processing and industrial applications.

Retrieve, structure, clean, and curate materials data from literature, synthetic datasets, experiments, and other sources.

Use Python-based workflows for data treatment, model execution, input preparation, output analysis, and visualization.

Test AI software outputs and benchmark results against other simulation or modeling tools.

Communicate model behavior, limitations, and results clearly to both technical and non-technical stakeholders.

Contribute to documentation, testing, validation reports, and technical decision-making.

What we are looking for

We are looking for someone with a strong background in materials science, computational materials science, or physical metallurgy.

The ideal candidate has:

A PhD in Materials Science, Metallurgy, Computational Materials Science, or a related field; or an MSc with relevant experience in materials modeling.

Strong understanding of physical metallurgy, preferably including steels, heat treatment, phase transformations, microstructure evolution, and process-property relationships.

Experience developing, using, or validating computational models for materials behavior.

Familiarity with materials data, alloy compositions, thermal histories, transformation kinetics, or microstructure-property relationships.

Ability to use Python for scientific scripting, data treatment, and model prototyping.

Strong communication skills and the ability to explain complex materials concepts in a multidisciplinary team.

Nice to have

Experience with any of the following would be highly valuable:

Steel phase-transformation modeling, TTT/CCT diagrams, JMAK kinetics, carbide precipitation.

CALPHAD, pycalphad, or similar tools.

Alloy design, ICME workflows, ML applied to materials science.

Product ownership, technical leadership, or experience translating scientific models into user-facing tools.

Data analysis using NumPy, pandas, matplotlib, scikit-learn, Excel-based workflows, or similar tools.

This role could be a strong fit if you

Recently completed a PhD involving computational or experimental materials modeling.

Have an MSc and several years of experience building or using materials models.

Enjoy combining materials science with scripting, data analysis, and practical software development.

Want to work close to product development rather than only research.

Are excited about helping shape digital tools for the future of steel and advanced materials.

Why join Ferritico?

At Ferritico, you will be part of a Swedish software startup working at the frontier of materials science, AI, and industrial digitalization. You will have the opportunity to influence both the scientific foundation and the product direction of tools used for advanced materials development and manufacturing.

We value teamwork, curiosity, technical excellence, and clear communication.

Not sure you meet every requirement?

We encourage you to apply even if your experience does not match every qualification listed above. We value diverse backgrounds, different perspectives, and people who are motivated to learn and contribute.

How to apply

Please send your CV and a short note describing your motivation for the role, along with your relevant experience in materials science, metallurgy, computational modeling, or materials informatics, to: contact@ferritico.com (Please include the job title in the email subject line)

Ansök till tjänsten

Senior Materials Informatics Engineer

Denna arbetsplats har annonserats på Arbetsförmedlingen-tjänsten den 2026-07-13 och publicerades av Arbetsförmedlingen.

OM FÖRETAGET

Ferritico AB

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