Deep Learning for Phylogenetic Inference

Deep Learning for Phylogenetic Inference

The research team will use deep neural networks to infer molecular phylogenies and extract phylogenetically useful patterns from amino acid or nucleotide sequences, which will help understand evolutionary mechanisms and build evolutionary models for a variety of...
Teaching Autonomous Soft Machines to Swim

Teaching Autonomous Soft Machines to Swim

The graceful swimming of a jellyfish, the locomotion of a snail, and the beating of our hearts are inspiring examples of machines made from soft materials. While examples abound in nature, we lack the technology to fabricate our own soft machines. The great promise of...
Exploring Quantum Embedding Methods for Quantum Computing

Exploring Quantum Embedding Methods for Quantum Computing

The research team will design quantum embedding algorithms that can be early adopters of quantum computers on development of advanced materials for possible applications in modern batteries, next-generation oxide electronics, or high-temperature superconducting power...

Mark your calendar for the MICDE SciFM 2024 Conference on April 2nd & 3rd, 2024!

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