Head of AI Structural Biology Research (Remote) (WA)Key Responsibilities: Lead and oversee a team of 4-6 AI/ML researchers, providing technical direction and promoting a culture of creativity and innovation.Drive the development and implementation of cutting-edge AI/ML models and algorithms, with a focus on amino acid sequence generation and 3D protein structure prediction.Collaborate with cross-functional teams of lab scientists, program managers, and software engineers to set research goals and translate discoveries into real-world applications.Manage and prioritize multiple research initiatives, ensuring they align with organizational objectives and timelines.Contribute to the design and architecture of AI systems, balancing research exploration with the needs of production-level implementations.Serve as a thought leader within the team, particularly in areas related to antibody engineering methodologies.Mentor and support the growth of team members as AI researchers and engineers.Represent the organization's AI research capabilities at conferences, in scientific publications, and through collaborations with academic and industry partners.Uphold and ensure adherence to the company's core values across all projects and interactions.Qualifications: Ph.D. in Computer Science, Machine Learning, Computational Biology, or a related field.Over 5 years of experience in AI/ML research, with at least 2 years in a leadership or technical lead capacity.Strong track record of publications or demonstrated expertise in areas such as generative AI, deep learning, or computational biology.Experience applying AI methodologies to biological challenges, particularly in protein design or drug discovery.Proven experience leading AI research projects and successfully transitioning research into practical solutions.Excellent communication skills, capable of explaining complex AI concepts to various audiences.Strong analytical and problem-solving abilities, with a critical mindset towards AI research challenges.Preferred Qualifications: Experience with large-scale multi-node training on HPC GPU clusters or in cloud environments like AWS.Familiarity with NGS, SPR, or Flow Cytometry data analysis.Previous experience managing AI research teams.
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