Head of AI Structural Biology Research (Remote)

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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