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Job DescriptionJob Description
About the role:
We are seeking a Research Scientist to help shape the future of AI-enabled drug discovery at Takeda, with a focus on structure-guided small-molecule design. Working across AI/ML, structural biology, and medicinal chemistry, you will develop cutting-edge computational approaches to explore chemical space more effectively and translate scientific advances into life-saving therapeutic impact.
How you will contribute:
- Develop and iterate on deep learning models across the molecular modeling stack — structure prediction, protein–ligand co-folding, affinity, and/or generative design — building on the latest research from the field.
- Design and execute rigorous benchmarking and evaluation pipelines that connect offline metrics to real-world performance and hold models to a high scientific bar.
- Partner with senior scientists and engineers to integrate validated models into production-ready drug discovery workflows.
- Apply computational and data-analysis methods to structural and sequence datasets to generate insights that guide model development.
- Apply generative AI and predictive ML models to design and prioritize chemical matter for research projects.
- Communicate findings through internal scientific talks, technical write-ups, and contributions to peer-reviewed publications.
- Collaborate across multidisciplinary teams — ML engineers, structural biologists, and software engineers — to prototype and scale impactful solutions.
Skill and qualifications
- Ph.D. in Computational Biology, Biophysics, Computer Science, Computational Chemistry, or a related field, with a research focus in ML for molecular modeling (e.g., structure prediction, co-folding, affinity, or molecular design).
- Hands-on experience developing, training, and validating deep learning models, including architectures relevant to structural biology and chemistry (e.g., transformers, equivariant neural networks, diffusion models).
- Direct experience with modern structure prediction or co-folding methods (e.g., AlphaFold2/3, RoseTTAFold, Chai-1, Boltz) or comparable molecular ML systems.
- Strong proficiency in Python and modern ML frameworks (PyTorch and/or JAX).
- Demonstrated scientific rigor: the ability to design controlled experiments, interpret results critically, and iterate effectively on model development.
- Strong written and verbal communication skills, and the ability to collaborate in a fast-paced, multidisciplinary research environment.
Preferred experience:
- Postdoctoral or industry experience in structure prediction, structure-based drug design, or a related computational domain.
- Familiarity with binding affinity prediction, including structure-based or physics-informed approaches.
- Authorship of publications or preprints in relevant venues (e.g., NeurIPS, ICML, ICLR).
- Experience deploying ML workflows on public cloud infrastructure (GCP, AWS, or Azure) and/or GPU/HPC environments.
- Familiarity with agentic coding tools (e.g., Claude Code, Codex) to accelerate research prototyping.
Takeda Compensation and Benefits Summary
We understand compensation is an important factor as you consider the next step in your career. We are committed to equitable pay for all employees, and we strive to be more transparent with our pay practices.
For Location:
Boston, MAU.S. Base Salary Range:
$116,000.00 - $182,270.00The estimated salary range reflects an anticipated range for this position. The actual base salary offered may depend on a variety of factors, including the qualifications of the individual applicant for the position, years of relevant experience, specific and unique skills, level of education attained, certifications or other professional licenses held, and the location in which the applicant lives and/or from which they will be performing the job. The actual base salary offered will be in accordance with state or local minimum wage requirements for the job location.
For information about our benefits, please click here.
EEO Statement
Takeda is proud in its commitment to creating a diverse workforce and providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, parental status, national origin, age, disability, citizenship status, genetic information or characteristics, marital status, status as a Vietnam era veteran, special disabled veteran, or other protected veteran in accordance with applicable federal, state and local laws, and any other characteristic protected by law.
LocationsBoston, MAWorker TypeEmployeeWorker Sub-TypeRegularTime TypeFull timeJob Exempt
YesIt is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.Skills Required
- Ph.D. in Computational Biology, Biophysics, Computer Science, Computational Chemistry, or a related field, with research focused on machine learning for molecular modeling
- Hands-on experience developing, training, and validating deep learning models
- Experience with architectures such as transformers, equivariant neural networks, or diffusion models
- Direct experience with modern structure prediction or co-folding methods such as AlphaFold2/3, RoseTTAFold, Chai-1, Boltz, or comparable systems
- Strong proficiency in Python and modern machine learning frameworks such as PyTorch or JAX
- Ability to design controlled experiments, critically interpret results, and iterate on model development
- Strong written and verbal communication skills
- Ability to collaborate in a fast-paced, multidisciplinary research environment
- Postdoctoral or industry experience in structure prediction, structure-based drug design, or a related computational domain
- Familiarity with binding affinity prediction, including structure-based or physics-informed approaches
- Authorship of publications or preprints in relevant venues such as NeurIPS, ICML, or ICLR
- Experience deploying machine learning workflows on GCP, AWS, Azure, or GPU/HPC environments
- Familiarity with agentic coding tools such as Claude Code or Codex
Takeda Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Takeda and has not been reviewed or approved by Takeda.
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Retirement Support — Employer-funded retirement is described as notably strong, combining a dollar-for-dollar 401(k) match with an additional company contribution that scales with age and service. Access to an employee stock purchase plan further supports long-term wealth building.
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Parental & Family Support — Paid bonding leave for all parents, substantial adoption/surrogacy reimbursement, and robust caregiver resources (backup care and Maven family-forming support) are emphasized as core strengths. These offerings create a comprehensive safety net for a range of family situations.
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Healthcare Strength — Multiple medical plan options (nationwide PPO/HSA and regional HMOs), employer HSA funding, and integrated mental-health and well-being programs signal depth in coverage. Preventive care is covered in-network, and plan choices by state expand access.
Takeda Insights
What We Do
For over 240 years, Takeda’s propensity to evolve has driven the next generation of innovation, and as a future-focused organization, we’re continuing to drive forward with endurance in our steadfast pursuit to achieve the best outcomes for our patients in a rapidly changing world. We have been preparing for this period of value creation by investing in data, digital and technology, and we’re proud of our employees and their commitment to turning groundbreaking ideas into life-changing impacts. Since our founding in Japan, integrity and putting patients first have been at the heart of our identity, and we will emerge ready for our future as one of the most trusted and science-driven digital biopharmaceutical companies. Join a team where your innovation impacts lives. Together, we’ll realize improved outcomes by improving data quality, enhancing launch execution and improving the patient journey. You’ll play a critical role in accelerating data collection and increasing accuracy across all parts of the business. Patients across the globe will benefit from access to treatments afforded by greater opportunities and efficiency in our research and development.
Why Work With Us
We connect to our history and Japanese heritage through everything we do to bring our purpose, values, vision, and imperatives to life. We are committed to bringing better health and a brighter future to patients. Being a part of Takeda means having the opportunity to be a part of something bigger than yourself.
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