Machine Learning group aims to push the frontier of artificial intelligence from algorithms, applications, and theory, to accelerate the exploration in natural science and industrial application. Machine Learning group developed many popular open-source machine learning toolkit, such as Graphormer, LightGBM, and so on, won a series of champions of international challenges, and published hundreds of high-quality papers.
Participate in the research project of AI for Science, write high-quality papers, deploy the advanced algorithms and models, develop and maintain open-source toolkit. Research topics including but not limited:
- Molecular modeling based on deep learning, including molecular dynamics, molecular property prediction, molecule generation, retrosynthesis, etc.
- Innovation of deep learning algorithms, e.g., graph neural networks, large-scale pre-training.
- Deep learning for material discovery, drug discovery, etc.
- Deep learning for wet experiments.
- Deep learning accelerated density functional theory.
- Solid mathematical knowledge.
- Solid domain knowledge for related research directions.
- Be good at deep learning library, e.g., PyTorch, Tensorflow.
- Publications on top machine learning conference. Or
- Solid computational physical, chemical, or biological knowledge, be good at quantum chemistry software.
- At least 12 months internship.
Required Internship Duration:
At least 6 months.
To learn more about Stars of Tomorrow Internship Program, please contact MSRAih@microsoft.com. We are happy to answer any question you may have.