Applied AI Research Scientist

About the role

The Applied AI Research Scientist will work at the intersection of machine learning and molecular science to advance drug discovery. This role involves a balance of developing cutting-edge ML models for molecular property prediction and applying these models to drive decision-making in internal and partnered drug discovery programs. The successful candidate will collaborate closely with multidisciplinary teams of chemists, biologists, and engineers to translate research into actionable therapeutic insights.

Responsibilities

• Design and implement novel Deep Learning algorithms including GNNs, generative, and physics-based models.
• Take part in cutting-edge research and bibliographic exploration.
• Collaborate with research and drug discovery teams to translate models into actionable insights.
• Develop robust ML models from molecular and biological data.
• Collaborate with chemists and biologists to deliver results that drive compound prioritization.
• Own ML workstreams from start to finish including goals, timelines, and stakeholder communication.
• Deliver models and predictions that scientists can use in their everyday workflows.

Required skills

• Deep Learning
• GNNs
• PyTorch
• TensorFlow
• Scikit-learn
• Python
• Scientific computing
• Machine Learning

Nice to have

• Drug discovery
• Computational chemistry
• Physics
• Generative models
• Diffusion models
• VAEs
• Autoregressive models
• Structure-based drug design
• Protein-ligand interactions
• HPC

Qualifications

• MSc or PhD in Computer Science, Machine Learning, Computational Chemistry, or related field
• 3-5 years of experience applying ML in scientific or industrial settings

About the Company

AQEMIA is a drug invention company dedicated to creating entirely new medicines to address major unmet medical needs. The company uses its proprietary QEMI platform, which combines physics-based modeling, statistical mechanics, and generative AI to design novel drug candidates from first principles.