By clicking the Apply button I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takedas Privacy Notice and Terms of Use. I further attest that all information I submit in my employment application is true to the best of my knowledge.
Job Description
Position Overview
We are seeking a hands-on collaborative AI/ML leader to accelerate the adoption and application of AI/ML capabilities at Takedas Japan research site. This role has two primary mandates:
- Enable AI/ML applicationto support target identification validation and mechanistic understanding across discovery programs
- Build local AI/ML capabilitiesby mentoring computational biologists and bioinformaticians in modern methods and agentic frameworks
You will be a key partner within the research organization working closely with discovery scientists and a global team of computational AI and data scientists to translate cutting-edge AI/ML approaches into practical tools that advance research programs. You will ensure the site can effectively leverage enterprise AI/ML platforms while adapting solutions to local scientific priorities. This role requires a leader who can bridge technical depth with scientific application understanding both the capabilities of modern AI/ML and the realities of drug discovery workflows.
Key Responsibilities
1. AI/ML Application to Research & Discovery
- Partner with computational biologists bioinformaticians and experimental scientists to apply AI/ML methods supporting target identification validation and mechanistic understanding
- Drive adoption of modern AI/ML approaches (representation learning predictive modeling causal inference) across multi-omics imaging clinical and real-world data
- Provide hands-on technical guidance across programs: recommend appropriate methods support implementation and review outputs for scientific rigor
- Partner with research project leaders to identify high-value opportunities for AI/ML application and prioritize efforts
2. Agentic Frameworks & Workflow Automation
- Evaluate implement and operationalize agentic AI frameworks (e.g. LLM-based research agents automated literature mining hypothesis generation pipelines) to accelerate discovery workflows
- Design and deploy automated workflows that chain tools data sources and models to streamline hypothesis generation experiment design and data analysis
- Establish best practices and governance for responsible reproducible AI use in research applications
3. Site Partnership & Global Alignment
- Act as key AI/ML liaison between the Japan site and global R&D computational functions; ensure alignment with enterprise AI strategy
- Represent site needs in global project teams and governance forums
- Communicate complex AI/ML concepts clearly to diverse scientific and non-technical stakeholders
4. Capability Building & Culture
- Mentor and upskill computational biologists and bioinformaticians in AI/ML methodologies and tool adoption
- Stay current with cutting-edge AI/ML and discovery technologies; translate external innovation into practical applications
- Champion new ways of working powered by digital automation and AI tools
Qualifications
Required:
- Expected: PhD in Computational Biology Bioinformatics Data Science Computer Science or related quantitative discipline with 8 years (AD) / 12 years (Director) relevant experience
- Proven track record of applying AI/ML methods to drug discovery or life sciences research
- Hands-on proficiency with ML/DL frameworks (PyTorch TensorFlow) and cloud-based compute environments
- Experience with multi-omics data analysis and integration
- Demonstrated ability to translate complex computational concepts for diverse scientific audiences
- Effective collaboration skills in matrixed global environments
Preferred:
- Familiarity with therapeutic area disease biology relevant to site priorities
- Working knowledge of LLMs agentic architectures and workflow orchestration tools
- Experience mentoring scientists with varying computational backgrounds
- Japanese language proficiency; cross-cultural collaboration experience
Additional Information
- The position will be based in Shonan Japan
Takeda Compensation and Benefits Summary:
Allowances: Commutation Housing Overtime Work etc.
Salary Increase: Annually Bonus Payment: Twice a year
Working Hours: Headquarters (Osaka/ Tokyo) 9:00-17:30 Production Sites (Osaka/ Yamaguchi) 8:00-16:45 (Narita) 8:30-17:15 Research Site (Kanagawa) 9:00-17:45
Holidays: Saturdays Sundays National Holidays May Day Year-End Holidays etc. (approx. 123 days in a year)
Paid Leaves: Annual Paid Leave Special Paid Leave Sick Leave Family Support Leave Maternity Leave Childcare Leave Family Nursing Leave.
Flexible Work Styles: Flextime Telework
Benefits: Social Insurance Retirement and Corporate Pension Employee Stock Ownership Program etc.
Important Notice concerning working conditions:
Locations
Fujisawa Japan
Worker Type
Employee
Worker Sub-Type
Regular
Time Type
Full time
Required Experience:
Director
By clicking the Apply button I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takedas Privacy Notice and Terms of Use. I further attest that all information I submit in my employment appl...
By clicking the Apply button I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takedas Privacy Notice and Terms of Use. I further attest that all information I submit in my employment application is true to the best of my knowledge.
Job Description
Position Overview
We are seeking a hands-on collaborative AI/ML leader to accelerate the adoption and application of AI/ML capabilities at Takedas Japan research site. This role has two primary mandates:
- Enable AI/ML applicationto support target identification validation and mechanistic understanding across discovery programs
- Build local AI/ML capabilitiesby mentoring computational biologists and bioinformaticians in modern methods and agentic frameworks
You will be a key partner within the research organization working closely with discovery scientists and a global team of computational AI and data scientists to translate cutting-edge AI/ML approaches into practical tools that advance research programs. You will ensure the site can effectively leverage enterprise AI/ML platforms while adapting solutions to local scientific priorities. This role requires a leader who can bridge technical depth with scientific application understanding both the capabilities of modern AI/ML and the realities of drug discovery workflows.
Key Responsibilities
1. AI/ML Application to Research & Discovery
- Partner with computational biologists bioinformaticians and experimental scientists to apply AI/ML methods supporting target identification validation and mechanistic understanding
- Drive adoption of modern AI/ML approaches (representation learning predictive modeling causal inference) across multi-omics imaging clinical and real-world data
- Provide hands-on technical guidance across programs: recommend appropriate methods support implementation and review outputs for scientific rigor
- Partner with research project leaders to identify high-value opportunities for AI/ML application and prioritize efforts
2. Agentic Frameworks & Workflow Automation
- Evaluate implement and operationalize agentic AI frameworks (e.g. LLM-based research agents automated literature mining hypothesis generation pipelines) to accelerate discovery workflows
- Design and deploy automated workflows that chain tools data sources and models to streamline hypothesis generation experiment design and data analysis
- Establish best practices and governance for responsible reproducible AI use in research applications
3. Site Partnership & Global Alignment
- Act as key AI/ML liaison between the Japan site and global R&D computational functions; ensure alignment with enterprise AI strategy
- Represent site needs in global project teams and governance forums
- Communicate complex AI/ML concepts clearly to diverse scientific and non-technical stakeholders
4. Capability Building & Culture
- Mentor and upskill computational biologists and bioinformaticians in AI/ML methodologies and tool adoption
- Stay current with cutting-edge AI/ML and discovery technologies; translate external innovation into practical applications
- Champion new ways of working powered by digital automation and AI tools
Qualifications
Required:
- Expected: PhD in Computational Biology Bioinformatics Data Science Computer Science or related quantitative discipline with 8 years (AD) / 12 years (Director) relevant experience
- Proven track record of applying AI/ML methods to drug discovery or life sciences research
- Hands-on proficiency with ML/DL frameworks (PyTorch TensorFlow) and cloud-based compute environments
- Experience with multi-omics data analysis and integration
- Demonstrated ability to translate complex computational concepts for diverse scientific audiences
- Effective collaboration skills in matrixed global environments
Preferred:
- Familiarity with therapeutic area disease biology relevant to site priorities
- Working knowledge of LLMs agentic architectures and workflow orchestration tools
- Experience mentoring scientists with varying computational backgrounds
- Japanese language proficiency; cross-cultural collaboration experience
Additional Information
- The position will be based in Shonan Japan
Takeda Compensation and Benefits Summary:
Allowances: Commutation Housing Overtime Work etc.
Salary Increase: Annually Bonus Payment: Twice a year
Working Hours: Headquarters (Osaka/ Tokyo) 9:00-17:30 Production Sites (Osaka/ Yamaguchi) 8:00-16:45 (Narita) 8:30-17:15 Research Site (Kanagawa) 9:00-17:45
Holidays: Saturdays Sundays National Holidays May Day Year-End Holidays etc. (approx. 123 days in a year)
Paid Leaves: Annual Paid Leave Special Paid Leave Sick Leave Family Support Leave Maternity Leave Childcare Leave Family Nursing Leave.
Flexible Work Styles: Flextime Telework
Benefits: Social Insurance Retirement and Corporate Pension Employee Stock Ownership Program etc.
Important Notice concerning working conditions:
Locations
Fujisawa Japan
Worker Type
Employee
Worker Sub-Type
Regular
Time Type
Full time
Required Experience:
Director
View more
View less