March 21, 2024, 10:17 a.m. | MIT News

ΑΙhub aihub.org

A new computational pipeline developed over three years efficiently identifies stiff and tough microstructures suitable for 3D printing in a wide range of engineering applications. The approach greatly reduces the development time for high-performance microstructure composites and requires minimal materials science expertise. Image credit: Alex Shipps/MIT CSAIL. By Rachel Gordon Every time you smoothly drive […]

3d printing alex applications articles computational credit csail development engineering every expertise image machine machine learning materials materials science mit mit csail performance pipeline printing rachel science

Software Engineer for AI Training Data (School Specific)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Python)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Tier 2)

@ G2i Inc | Remote

Data Engineer

@ Lemon.io | Remote: Europe, LATAM, Canada, UK, Asia, Oceania

Artificial Intelligence – Bioinformatic Expert

@ University of Texas Medical Branch | Galveston, TX

Lead Developer (AI)

@ Cere Network | San Francisco, US