Remote Principal Research Scientist - AI in Drug Discovery

Our client is seeking a highly motivated and innovative Principal Research Scientist to lead AI initiatives in drug discovery. This is a fully remote position, offering the flexibility to work from anywhere within the US. You will be instrumental in leveraging artificial intelligence and machine learning to accelerate the identification and development of novel therapeutics. This role requires a deep understanding of both biological processes and advanced computational techniques. You will be responsible for developing and implementing AI models for target identification, hit-to-lead optimization, and predictive toxicology. Collaborating with cross-functional teams including biologists, chemists, and software engineers, you will translate complex scientific challenges into data-driven solutions. The ideal candidate will have a proven track record of success in applying AI/ML to biological or chemical data, with a strong emphasis on practical application in a research setting. Responsibilities include conceptualizing and designing AI/ML projects, performing rigorous model evaluation, and ensuring the scalability and interpretability of developed solutions. You will also stay abreast of the latest advancements in AI and computational biology, identifying opportunities to integrate new methodologies into our research pipeline. A PhD in Computer Science, Bioinformatics, Computational Chemistry, or a related field is required, along with significant post-doctoral or industry experience. Exceptional programming skills in Python and proficiency with ML libraries (e.g., TensorFlow, PyTorch) are essential. Experience with large-scale biological datasets and cheminformatics tools is highly advantageous. As a remote-first role, you will need excellent self-management, communication, and collaboration skills to thrive in a distributed team environment. Participation in virtual team meetings, contributions to shared documentation, and proactive engagement with colleagues are crucial for success.

Key Qualifications:
PhD in a relevant quantitative field with substantial AI/ML experience. Expertise in Python and major machine learning frameworks. Demonstrated ability to apply AI/ML to drug discovery challenges. Strong understanding of biological or chemical principles. Excellent problem-solving and analytical skills. Proven ability to work independently and collaboratively in a remote setting. Experience with cloud-based AI/ML platforms.