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Job Description

Position Overview

At Takeda, we are a forward-looking, world-class R&D organization that unlocks innovation and delivers transformative therapies to patients. By focusing R&D efforts on our core therapeutic areas and pioneering AI-driven platforms, we aim to accelerate the next generation of biologics discovery.

We are seeking an innovative and dynamic **Senior Scientist** with a strong background in **computational biology, structural bioinformatics, and machine learning** , particularly as applied to **antibody and large molecule design** . You will join our Large Molecule AI/ML team and contribute to a multidisciplinary group that integrates **state-of-the-art AI with experimental strategies** to drive therapeutic breakthroughs in oncology, neuroscience, and inflammatory diseases.

This execution-focused role will involve applying AI/ML and structural modeling techniques to design, optimize, and validate biologics, including antibodies, enzymes, and antibody-drug conjugates (ADCs).

Key Responsibilities

+ **Develop and implement AI/ML models** for sequence- and structure-based design of biologics, with emphasis on generative frameworks (e.g., diffusion models, inverse folding, LMs).

+ Apply and extend tools such as **Boltz** , **Rosetta, AlphaFold2, ESMFold, ProteinMPNN** , and other foundational models for **de novo antibody discovery, affinity maturation, and developability optimization** .

+ Build and optimize predictive models for multiple objectives (e.g., solubility, immunogenicity, thermostability, epitope specificity) based on NGS, in vitro, and in vivo datasets.

+ **Integrate 3D structural data** into model-guided protein design pipelines.

+ Collaborate with experimental scientists to inform hypothesis generation, **model validation** , and iterative learning in Design–Make–Test–Analyze cycles.

+ Manage and process large-scale experimental and synthetic datasets for model training, benchmarking, and deployment.

+ Prototype and deploy ML pipelines using best practices in software engineering and reproducibility

+ Stay current with the latest developments in NLP, structural modeling, and AI for protein science; evaluate emerging tools for integration.

+ Clearly communicate complex ideas to technical and non-technical audiences and contribute to internal knowledge sharing.

Required Qualifications

+ PhD degree in **Computational Biology, Structural Biology, Machine Learning, or related fields** (or equivalent) with 2+ years relevant experience, or MS with 8+ years relevant experience, or BS with 10+ years relevant experience

+ Demonstrated ability to **build and apply ML models** (deep learning, protein LMs, GNNs) to biological or structural datasets.

+ Hands-on experience with **antibody design or protein engineering** , especially using ML-guided or structure-aware methods.

+ Strong understanding of protein structure and dynamics, including **MD simulation, FEP, Rosetta modeling, or AlphaFold-based tools** .

+ Proficiency in Python and ML libraries (e.g., PyTorch, scikit-learn, NumPy); familiarity with Unix command line tools and scripting.

+ Strong data wrangling and visualization skills; ability to translate modeling outputs into actionable insights for bench scientists.

+ Excellent interpersonal and written communication skills; thrives in a highly collaborative environment.

Preferred Qualifications

+ Experience developing or fine-tuning generative models for protein design (e.g., RFdiffusion, ProGen, ESM-IF, ProteinMPNN).

+ Prior application of **structure-guided ML** to engineer antibodies, antigens, or binders against defined epitopes.

+ Familiarity with **large-scale structural datasets** (PDB, EMDB) and bioinformatics tools for sequence/structure analysis.

+ Exposure to **wet-lab data integration** and cross-functional collaboration with experimental biologists.

+ Experience building reproducible workflows using **Docker/Singularity, Nextflow** , or similar tools.

+ Understanding of biologic drug properties (developability, immunogenicity, CMC constraints).

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

$137,000.00 - $215,270.00

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.

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._

Locations

Boston, MA

Worker Type

Employee

Worker Sub-Type

Regular

Time Type

Full time

Job Exempt

Yes

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