We are Ferritico, a Swedish machine learning software company disrupting the global steel industry. Based on more than 10 years of leading KTH steel research we are developing machine learning steel properties and process simulation SaaS. The Ferritico service digitalizes the processes of developing, manufacturing and implementing steel, helping our customers to significantly cut time and costs.

We aggregate large sets of steel properties and process data and apply physical-based and machine learning models enabling our customers to predict and view correlations in data when optimizing materials, products and processes. Ferritico is well funded through support from i.a. EIT and Vinnova although already generating revenues. Ferritico is currently strengthening the team with a Materials Informatics Engineer as a consequence of increased development and service demand.

The Opportunity

This employment constitutes a unique opportunity to join the Ferritico team in central Stockholm and to step up your game as an engineer within materials science where informatics, i.e. data and computational modelling is key.

As a Materials Informatics Engineer you will be outlining our customer’s steel processes and identifying materials and process data correlations enabling process and product optimization. You will identify and implement state-of-the-art tools, including machine learning based, and methods to identify and extract data from open literature sources as well as providing our customers a secure and robust platform for data pooling.

You will establish a data-driven and systematic work pattern for aggregation, quality control and maintenance of data coming from multiple sources in different formats and work creatively to leverage physical models to generate complementary synthetic data. You will structure the data for the purpose of machine learning  model learning and contribute to testing and refining the models through identification of data set deficiencies. Your work will foster the highly profitable shift towards data-driven and simulation based work patterns within steel development and manufacturing and include:

• Conducting strategic pre-studies where customer processes are explored focusing on materials data correlations and optimization possibilities

  
  

• Identify, evaluate, customize and implement out-of-the-box software solutions and libraries for data document retrieval and extraction or develop in-house software for the purpose

  
  

• Define requests for proposal and requirement specifications for off-shore data collection collaborations and continuously steer our partners' work  

  
  

• Create strategies and tools for data maintenance and implement quality assurance metrics that can be validated continuously and automatically

  
  

• Test machine learning software prediction output and benchmark results against other simulation tools 

  
  

• Attend and prepare presentation material for customer and partner project meetings  

You are passionate

about developing state-of-the-art steel alloys and digital solutions using the latest technology. You embrace the importance of maintaining data quality through your accurate and data-driven approach and is inspired by the opportunity to contribute to and learn from related competence fields.

Requirements:

• MSc, PhD, or equivalent experience in material science or similar

  
  

• Exceptional communication skills. Fluent in written and spoken English

  
  

• Professional experience from materials engineering, preferably from the steel industry

  
  

• Programming experience, e.g. scripting preferably using Python and data management libraries and tools like Pandas and Jupyter, as wells as SQL.

  
  

• Rigorous attention to detail and focus on timely high-quality deliverables

  
  

• Swedish work permit

Meriting skills:

• Interest in or experience from statistical modeling and machine learning

  
  

• Experience from using materials and process simulation software, e.g. FEM or thermodynamics-based modelling with CALPHAD or similar.