Takeda · 1 day ago
Research Scientist, AI/ML Biologics - Methods Development - Method
Takeda is a forward-looking, world-class R&D organization that unlocks innovation and delivers transformative therapies to patients. They are seeking a skilled and motivated Scientist to join their Large Molecule AI/ML team, focusing on developing and applying machine learning methods to accelerate antibody discovery and optimization on active pipeline projects.
BiotechnologyHealth CareManufacturingMedicalPharmaceutical
Responsibilities
Develop and implement machine learning models for antibody property prediction, including developability attributes (stability, aggregation, immunogenicity, viscosity) to support active discovery programs
Build predictive tools that rank antibody candidates, flag potential liabilities, and suggest sequence modifications for improved properties
Benchmark and evaluate external computational methods and commercial AI platforms; recommend best-in-class tools for integration into internal workflows
Innovate, develop, and apply predictive models for protein design and developability engineering, utilizing large-scale NGS, in vitro, in vivo and other proprietary in-house and external data sources
Investigate transfer learning and few-shot learning approaches to enable rapid model deployment on new antibody formats (multi-specifics, VHH, ADCs) with limited training data
Collaborate with experimental teams to validate predictions against assay data, iterate on model development, and integrate AI/ML outputs into Design-Predict-Make-Confirm cycles
Establish and maintain AI performance dashboards and KPIs to track prediction accuracy, model reliability, and impact on project timelines
Stay current with advances in machine learning for protein science and contribute to internal knowledge sharing
Qualification
Required
PhD in Computational Biology, Bioinformatics, Computer Science, or related field, OR MS with 6+ years relevant experience, OR BS with 10+ years relevant experience
Proven track record in developing machine learning models for biological or chemical data
Proficiency in Python and machine learning frameworks (PyTorch, TensorFlow, or scikit-learn)
Experience with protein sequence analysis and understanding of antibody structure-function relationships
Strong analytical and problem-solving skills with demonstrated ability to work both independently and collaboratively
Excellent communication skills to convey complex computational concepts to diverse scientific audiences
Preferred
Experience with protein language models (ESM, ProtTrans) or other deep learning architectures for protein property prediction
Familiarity with antibody developability assessment (stability, aggregation, immunogenicity)
Experience with transfer learning or active learning approaches
Prior experience in pharmaceutical or biotech R&D environment
Experience with cloud computing (AWS, GCP) and version-controlled ML pipelines
Benefits
Short-term and/ or long-term incentives
Medical, dental, vision insurance
401(k) plan and company match
Short-term and long-term disability coverage
Basic life insurance
Tuition reimbursement program
Paid volunteer time off
Company holidays
Well-being benefits
Up to 80 hours of sick time
Up to 120 hours of paid vacation
Company
Takeda
Takeda is a biopharmaceutical company that researches and develops pharmaceutical drugs.
H1B Sponsorship
Takeda has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (45)
2024 (39)
2023 (38)
2022 (34)
2021 (44)
2020 (18)
Funding
Current Stage
Public CompanyTotal Funding
$2.46B2025-06-27Post Ipo Debt· $2.4B
2016-09-01Grant· $19.8M
2016-05-08Grant· $38M
Leadership Team
Recent News
2026-01-07
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