Master's degree or equivalent work experience in deep learning and reinforce learning, with publications in top ML conferences, e.g., NeurIPS, ICLR, ICML.
Passion for science related problems, including but not limited to, materials science, chemistry, physics, and biology.
Proficiency in Python and relevant ML libraries (e.g., PyTorch).
Experience with transformer-based models (e.g., GPT, Llama).
Fluency in spoken and written English.
Demonstrable capabilities in doing solid research in machine learning evidenced by high quality publications and/or a track record of innovation.
Candidates must be able to collaborate effectively with other researchers. We are particularly interested in the candidates who can work across disciplinary boundaries
Preferred Qualifications:
Good chemistry, physics, biology, and medicine implementation skills and mathematical background are good to have but not a must.
Candidates must be able to collaborate effectively with other researchers. We are particularly interested in the candidates who can work across disciplinary boundaries.
Responsibilities
Perform cutting-edge research in collaboration with other researchers and engineers.
Passion and dedication in machine learning for science, and your commitment to doing world-class research. Stay current with the latest trends, research, and developments in AI and machine learning to ensure our systems remain at the forefront of innovation.