The objective is to achieve a predefined confidence level across the compositional region of interest. At the same time, the number of additional calculations should be minimized and compositions with the best trade-off between hardness and toughness identified.
Project plan
Weeks 1-2: Literature review and project definition
Weeks 3-4: Existing workflow and database - baseline model and uncertainty assessment
Weeks 5 -12: Active-learning method development and implementation
Weeks 13-15: Final analysis and documentation
Weeks 16-20: Writing thesis and preparing presentation
Location
The position is based in Västberga, Stockholm.
Profile
We are looking for a Master's student with a strong foundation in physics, materials science, applied mathematics, or computational engineering. The ideal candidate has experience with Python programming, scientific computing, data analysis, and machine learning. Knowledge of atomistic simulations, autoQMAS calculations, density functional theory (DFT), or computational materials science is meritorious. The project requires curiosity, initiative, and an interest in combining physics-based modelling with AI-driven approaches for accelerated materials design.
Our Culture
At Sandvik, we work with advanced technology and exciting innovations, but it is our people who are the true key to our success. We believe that diversity creates a better environment and that inclusion is essential to achieving strong results. This means supporting one another, sharing knowledge, and embracing each other's differences.
To learn more about us, we encourage you to visit our website, LinkedIn, or Facebook.
Scope
The master’s thesis project corresponds to 30 ECTS credits and is expected to be carried out full-time over approximately 20 weeks. The project is planned to start in January 2027.
Contact Information
For more information about the position, please contact Aayush Sharma, Senior R&D Professional +46 (0)70 616 79 47
We have carefully selected the recruitment channels and marketing methods we wish to use and kindly, but firmly, decline any additional contacts regarding these matters.
Application
Please submit your application no later than December 1, 2026. Click Apply and attach your CV and cover letter. Please note that we do not accept applications via email. Job ID: R0097769.
