AI Senior Scientist - Drug Discovery

Job Title: AI Senior Scientist - Drug DiscoveryLocation: SeattleEmployment Type: Full-time, On-siteSalary Range: $200,000- $250,000 per yearCompany Overview:A leading biopharmaceutical company is leveraging artificial intelligence (AI) and machine learning to accelerate drug discovery. With a strong pipeline spanning from discovery to clinical trials, we are seeking a highly skilled Scientist/Senior Scientist specializing in AI-driven small molecule drug design to join their research team.Position Summary:A Senior Scientist with expertise in computational structural biology and small molecule drug discovery. This role involves applying AI-driven techniques such as generative modeling, deep learning, and molecular docking to optimize lead compounds and enhance drug discovery efficiency. The successful candidate will collaborate closely with medicinal chemists, biologists, and computational scientists to integrate AI methodologies into our workflows.Key Responsibilities:Develop and implement AI-driven small molecule drug design pipelines for virtual screening, molecular property prediction, and lead optimization.Utilize advanced AI techniques such as generative modeling, deep learning, and reinforcement learning to identify novel drug candidates.Apply AI-enhanced molecular docking methods to improve binding affinity predictions and optimize lead compounds.Collaborate with cross-functional teams to integrate computational approaches into experimental workflows.Conduct large-scale virtual screening and analyze computational data to refine molecular properties.Contribute to the development of AI-based software tools and platforms for drug discovery.Stay updated with advancements in AI and computational chemistry.Required Qualifications:Ph.D. in Computational Chemistry, Bioinformatics, Biophysics, Machine Learning, or a related field.Minimum of 5 years of experience in AI-driven small molecule drug design or related computational fields.Strong background in AI and machine learning techniques applied to drug discovery.Expertise in molecular modeling and drug design software (e.g., AutoDock, Schrí¶dinger, Open Babel).Proficiency in programming languages such as Python, R, or C++, with experience in machine learning frameworks (e.g., TensorFlow, PyTorch).Experience analyzing large-scale molecular databases and conducting virtual screening.Strong communication skills for presenting complex computational findings.

Created: 2025-03-10