Takeda

Research Scientist, Molecular AI

Takeda$116K — $182K *
Pharmaceuticals & Biotech
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Ph.D. in Computational Biology, Biophysics, Computer Science, Computational Chemistry, or related field with focus on ML for molecular modeling.
  • Hands-on experience with developing deep learning models relevant to structural biology and chemistry.
  • Experience with modern structure prediction or co-folding methods like AlphaFold2/3 or RoseTTAFold.
  • Strong proficiency in Python and ML frameworks such as PyTorch or JAX.
  • Demonstrated scientific rigor in designing experiments and interpreting results critically.

Responsibilities

  • Develop deep learning models for molecular modeling tasks including structure prediction and generative design.
  • Design and execute benchmarking pipelines to connect model metrics to real-world performance.
  • Partner with scientists to integrate models into drug discovery workflows.
  • Apply computational methods to data sets for insights to guide model development.
  • Communicate findings through talks, technical write-ups, and peer-reviewed publications.
  • Collaborate with multidisciplinary teams to prototype and scale solutions.

Benefits

  • Medical, dental, and vision insurance coverage.
  • 401(k) plan with company match.
  • Tuition reimbursement program.
  • Paid volunteer time off and company holidays.
  • Up to 120 hours of paid vacation and 80 hours of sick time per calendar year.
Full Job Description
Job 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, MA

U.S. Base Salary Range:
$116,000.00 - $182,270.00

The 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.

U.S. based employees may be eligible for short-term and/ or long-term incentives. U.S. based employees may be eligible to participate in medical, dental, vision insurance, a 401(k) plan and company match, short-term and long-term disability coverage, basic life insurance, a tuition reimbursement program, paid volunteer time off, company holidays, and well-being benefits, among others. U.S. based employees are also eligible to receive, per calendar year, up to 80 hours of sick time, and new hires are eligible to accrue up to 120 hours of paid vacation.

Locations
Boston, MA

Worker Type
Employee

Worker Sub-Type
Regular

Time Type
Full time

Job Exempt
Yes

It 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.

About Takeda

Takeda Pharmaceutical Company Limited is a global pharmaceutical company that develops and markets pharmaceutical products. The company's products are used to treat a wide range of medical conditions, including cardiovascular and metabolic diseases, respiratory diseases, and cancer. Takeda Pharmaceutical Company Limited was founded in 1781 and is headquartered in Tokyo, Japan. The company has operations in more than 80 countries and employs more than 49,000 people worldwide.
Learn more about Takeda
Size
47,347 employees
Market Cap
$48.2 billion
Industry
Founded
1781
5 Year Trend
+15.6%
NASDAQ

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