Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

Design engineers can use AI-driven simulation to overcome bottlenecks and accelerate materials discovery with hybrid workflow ...

Real-world data (RWD) is transforming clinical research, augmenting existing randomized controlled trial (RCT) data to de-risk studies and improve generalizability. With regulators setting clearer ...

The field of particle physics is approaching a critical horizon defined by challenges including unprecedented data volumes and detector complexity. Upcoming ...

Microelectromechanical systems (MEMS) electrothermal actuators are widely used in applications ranging from micro-optics and ...

The performance of rechargeable batteries is governed by processes deep within their components. A fundamental understanding of electrochemistry, structure–property–performance relationships and the ...

Raja Shankar, VP of machine learning at IQVIA, discusses which AI capabilities sponsors are most likely to adopt first to ...

2026 will be a transformative year in this area — one where force fields redefine the boundaries of atomistic simulation, making previously unthinkable modeling and discoveries routine. With workflows ...

Key TakeawaysDigital twins are ultra-accurate computer-based simulations of complex physical systems used for exploring "what ...

The Department of Energy (DOE) has released specifications for 26 artificial intelligence (AI) challenges under its Genesis Mission that could reshape how ...

Torc, a pioneer in self-driving vehicle technology, today announced the expansion of its autonomous truck testing operations to public roads in Michigan using the latest-generation Daimler Truck ...