Master Thesis – Data-Efficient Exploration

Teknik, data och digitalt · Data, AI och analys · Datavetenskap · Maskininlärning · Dataanalys

I korthet

Sandvik is seeking a Master's student for a thesis project focused on data-efficient exploration of material compositions and mechanical properties using first-principles calculations and active learning. The project involves developing active-learning strategies to minimize calculation needs while identifying optimal material compositions. It is based in Västberga, Stockholm, and requires a background in physics, materials science, or computational engineering with experience in Python, data analysis, and machine learning.

Ansvarsområden

Develop active-learning strategies to reduce prediction uncertainty.
Identify a limited but sufficient set of informative compositions for additional autoQMAS calculations.
Iteratively incorporate newly generated data into a database to update and improve predictive models.
Achieve a predefined confidence level across the compositional region of interest.
Minimize the number of additional calculations.
Identify compositions with the best trade-off between hardness and toughness.

Krav

Master's student with a strong foundation in physics, materials science, applied mathematics, or computational engineering.
Experience with Python programming.
Experience with scientific computing.
Experience with data analysis.
Experience with machine learning.

Önskade kvalifikationer

Knowledge of atomistic simulations is meritorious.
Knowledge of autoQMAS calculations is meritorious.
Knowledge of density functional theory (DFT) is meritorious.
Knowledge of computational materials science is meritorious.
Curiosity, initiative, and an interest in combining physics-based modelling with AI-driven approaches for accelerated materials design.

Förmåner

Opportunity to complete a master's thesis on an advanced R&D topic.
Work with advanced technology and exciting innovations.
Contribute to the development of next-generation cutting tool materials.
Project duration of approximately 20 weeks, full-time (30 ECTS credits).

Färdigheter

Pythonscientific computingdata analysismachine learningatomistic simulationsautoQMAS calculationsdensity functional theorycomputational materials science

#Master Thesis#Data-Efficient Exploration#Materials Modelling#First-Principles Calculations#Active Learning#AI#Computational Materials Science#Stockholm

Om Sandvik

Sandvik is a global, high-tech engineering group providing solutions that enhance productivity, profitability and sustainability for the manufacturing, mining and infrastructure industries. We are at the forefront of digitalization and focus on optimizing our customers’ processes. Our world-leading offering includes equipment, tools, services and digital solutions for machining, mining, rock excavation and rock processing. In 2024, the Sandvik Group had approximately 41,000 employees, sales in more than 150 countries and revenues of about SEK 123 billion.

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