Hello potential international mentees, my name is Prof. Tzuhsiung Yang. An assistant professor at the Department of Chemistry, National Tsing Hua University, Hsinchu, Taiwan. My research interest lies in the interface of generative artificial intelligence (AI) models and quantum chemistry for molecules and materials design.
Hello potential international mentees, our lab is the Laboratory of Autonomous Molecule Design. We utilize generative AI models such as Variational Autoencoder (VAE), Diffusion Model (like OpenAI's Sora), and large language model (Bidirectional Encoder Representations from Transformer (BERT), etc) to design chemically sensible and property optimized molecules and materials.
Transition metal complexes: Semi-supervised variational autoencoder (SSVAE) is utilized to allow the simultaneous generation of ligands of transition metal complexes to optimize their properties towards spintronics, water oxidation catalysis, and many other properties.
small molecule cancer drugs: Semi-supervised variational autoencoder (SSVAE) is trained to learn about common features in FDA-approved small molecule cancer drugs and design similar drug-like molcules.
Molecular qubits: High-level wavefunction theory methods are used to predict properties of molecular qubits and generative AI models are used to design potential molecular qubits with optimized properties for quantum sensing.
Yushan Young Fellow, 2022
Ph.D., Chemistry, University of Wisconsin-Madison, 2018
2 Vacancies
Job Description
The intern will be trained with cutting edge techniques in generative AI model, gain experience and training in Python, the most used programming language, in addition to the scientific training in the related research topic.
Preferred Intern Education Level
Bachelor or enrolled college student
Skill sets or Qualities
- Experience level in Python and artificial intelligence.
- Good academic standing (if still in college).
- Eagerness to learn about skills and knowledge outside his/her background.