Key responsibilities:

1. Showcase expertise in scientific computer languages (e.g., Python), using deep learning libraries (e.g., Tensorflow, PyTorch), and cloud-based computing (AWS, Google Cloud, etc.) bonus
2. Apply multiple deep learning methods (Diffusion model, Transformer, GNN, GAN, RNN, CNN, etc.) or natural language processing (NLP) demonstrated by peer-reviewed publications or published projects
3. Use your strong math skills (e.g., statistics, algebra)
4. Work on data processing and analysis, with strong statistical skills with the most common frameworks (e.g., Numpy, Pandas, Matplotlib, Seaborn, Scikit-Learn, Keras)

5