Requirements

• PhD or equivalent practical experience in a technical field.
• A proven track record in machine learning using deep learning techniques.
• Strong knowledge of linear algebra, calculus, and statistics.
• Experience with ML frameworks like JAX, PyTorch, or TensorFlow.
• Passion for applying ML research to real-world problems.

Nice to Have

• PhD in machine learning or computer science.
• Relevant research experience such as post-doctoral roles or publications.
• Experience in scientific environment across disciplines.
• Experience with biological or chemical data and software.
• Experience with real-world datasets.
• Experience with ML on accelerators.
• Experience in areas like deep learning for drug discovery, computer vision, etc.

What You'll Be Doing

• Contribute to research directions in machine learning for drug discovery.
• Identify and create novel ML techniques and required data.
• Develop architectures and training algorithms of ML models.
• Analyze and tune experimental results for future directions.
• Implement and scale training and inference engineering frameworks.
• Report and present research findings clearly to different disciplines.
• Collaborate iteratively with scientists and domain experts.

Perks and Benefits

• Hybrid working model with 3 office days a week.
• Opportunity to work with an interdisciplinary team on groundbreaking innovation.
• Chance to contribute towards solving all disease with AI.
• Cultivate a diverse and inclusive research culture.
• Equal employment opportunities regardless of background.