Takeda is seeking an innovative leader to spearhead emerging research efforts in AI/ML-driven drug discovery with an initial focus on large molecule design
Requirements
- Ph.D. in computer science, statistics, computational biology, or a related field with a focus on machine learning
- 10+ years of research experience in AI/ML, computational drug design, structural modeling, or related disciplines within the pharmaceutical or biotechnology industry
- Demonstrated expertise in machine learning algorithms, deep learning architectures, transformer-based models, and statistical modeling as applied to molecular design and developability
- Proven track record in developing machine learning models for antibody design, protein–ligand co-folding, and/or related structural modeling approaches
- Proficiency with programming languages (e.g., Python, R, C++) and ML frameworks (e.g., PyTorch, Tensorflow) with experiencing scaling computational infrastructure for large model training in cloud environments
Responsibilities
- Develop and execute a research strategy that leverages AI/ML to advance drug discovery efforts with specific focus on de novo design and optimization of large molecules
- Stay abreast of emerging trends and technologies in AI/ML and their application to pharmaceutical research
- Drive integration of the modeling pipelines with internal data foundation platforms, building a continuous test-and-learn pipeline through experimental validation
- Oversee the planning, execution, and timely delivery of research projects, ensuring alignment with strategic milestones and corporate objectives
- Design partnership models where computational biology teams provide domain expertise while the AI/ML team delivers advanced methodological solutions
- Champion AI/ML approaches across computational sciences and Research, building cross-functional communities of practice
Other
- 15+ years experience, or MS with 21+ years experience, or BS with 23+ years experience
- Exceptional leadership, project management, and communication skills, with ability to translate complex computational insights to diverse scientific audiences and align with therapeutic portfolio priorities and R&D objectives
- Strong problem-solving aptitude and strategic thinking with an entrepreneurial mindset
- Ph.D. in computer science, statistics, computational biology, or a related field with a focus on machine learning
- U.S. based employees may be eligible for short-term and/or long-term incentives, medical, dental, vision insurance, a 401(k) plan and company match, and other benefits
