Data-driven science represents a transformative paradigm in materials science. Both data-driven materials science and informatics encompass systematic knowledge extraction from materials datasets.

Technologies that underpin modern society, such as smartphones and automobiles, rely on a diverse range of functional materials. Materials scientists are therefore working to develop and improve new ...

Kohei Noda, a researcher at JSR Corporation, and Professor Ryo Yoshida at the Institute of Statistical Mathematics, along with their research group, have developed an innovative machine learning ...

In data-driven research, the most crucial resource is data. However, compared to AI-advanced fields such as natural language processing, computer vision, biology, and medicine, the data resources in ...

The importance of digital tools and simulation for successful composite parts design is well established, whether for aircraft wings, automotive bumper beams or bicycle frames. Over the past decade, ...

Studying and designing novel materials is a central application of quantum mechanics. Chemists, materials scientists, and physicists focus on subtle interactions in quantum materials and to uncover ...

Both fields are in high demand, pay well, and lead to exciting, future-proof careers. If you're deciding between becoming a data scientist or an AI engineer, the choice often comes down to what ...

Data Science is a structured approach to extracting valuable insights from data, and it involves several key stages to ensure success. Let's explore each phase in detail: By following this structured ...