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 Takeda’s Privacy Notice (https://jobs.takeda.com/privacynotice) and Terms of Use (https://www.takeda.com/terms-and-conditions/) . 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 Takeda's Japan research site. This role has two primary mandates: + **Enable AI/ML application** to support target identification, validation, and mechanistic understanding across discovery programs + **Build local AI/ML capabilities** by 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:** + It is possible the job scope may change at the company’s discretion. + It is possible the department and workplace may change at the company’s discretion. **Locations** Fujisawa, Japan **Worker Type** Employee **Worker Sub-Type** Regular **Time Type** Full time