Research Senior Scientist, AI/ML (Biologics)
Takeda
3 months ago
Remote friendly (Boston, MA)
United States
$137,000 - $215,270 USD yearly
Clinical Research and Development
Position Overview:
- AI/ML Research Senior Scientist (Large Molecule AI/ML) focused on AI/ML for antibody discovery and design, integrating advanced computation with experimental strategies to drive large-molecule therapeutic breakthroughs and deepen disease biology understanding.
Key Responsibilities:
- Develop and implement state-of-the-art AI/ML for de novo antibody design/discovery, including fine-tuning protein language models and generative protein design.
- Develop, implement, and deploy ML algorithms for multi-objective optimization of antibodies, antigens, ADCs, and other biologics.
- Build tools for data incorporation from integrated Design-Predict-Make-Confirm cycles using automated experimental platforms generating quality data at scale.
- Innovate and apply predictive models for protein design and developability engineering using large-scale NGS plus in vitro/in vivo and other proprietary/external data.
- Manage and process large-scale biological datasets for model training and evaluation.
- Stay current with advancements in NLP, ML, and generative AI to build novel therapeutic discovery/development tools.
- Collaborate to optimize computational discovery infrastructure with individual and team-based solutions.
- Communicate complex scientific ideas to technical and non-technical audiences.
Qualifications:
- PhD (2+ years), MS (8+ years), or BS (10+ years) in a scientific discipline (or equivalent).
- Proven ML track record for chemical/biological data, including AI/ML-enabled molecular generation and affinity prediction.
- Experience modeling antibody/antigen sequence, structure, and interactions.
- Proficiency in Python and experience with cloud computing.
- Strong analytical/problem-solving skills; creative and collaborative.
- Ability to explain complex ideas to non-specialists; continuous improvement mindset.
- Learning agility and scientific curiosity; entrepreneurial, strategic problem-solving.
Preferred Qualifications & Skills:
- Experience with modern ML architectures for antibody design (LLMs, diffusion models, flow-matching, Bayesian Optimization, GNNs, etc.).
- Experience designing de novo binders for targets/epitopes.
- Experience analyzing NGS-derived antibody repertoires for sequence- and structure-based design.
- Experience with molecular simulation and conformational analysis.
Benefits (if part of job description):
- Eligible for medical/dental/vision insurance, 401(k) with company match, short-/long-term disability, basic life insurance, tuition reimbursement, paid volunteer time off, company holidays, well-being benefits, up to 80 hours sick time/year, and up to 120 hours paid vacation for new hires (U.S. employees).
- U.S. based employees may be eligible for short-term and/or long-term incentives.
Application Instructions:
- Apply via the “Apply” button.
- AI/ML Research Senior Scientist (Large Molecule AI/ML) focused on AI/ML for antibody discovery and design, integrating advanced computation with experimental strategies to drive large-molecule therapeutic breakthroughs and deepen disease biology understanding.
Key Responsibilities:
- Develop and implement state-of-the-art AI/ML for de novo antibody design/discovery, including fine-tuning protein language models and generative protein design.
- Develop, implement, and deploy ML algorithms for multi-objective optimization of antibodies, antigens, ADCs, and other biologics.
- Build tools for data incorporation from integrated Design-Predict-Make-Confirm cycles using automated experimental platforms generating quality data at scale.
- Innovate and apply predictive models for protein design and developability engineering using large-scale NGS plus in vitro/in vivo and other proprietary/external data.
- Manage and process large-scale biological datasets for model training and evaluation.
- Stay current with advancements in NLP, ML, and generative AI to build novel therapeutic discovery/development tools.
- Collaborate to optimize computational discovery infrastructure with individual and team-based solutions.
- Communicate complex scientific ideas to technical and non-technical audiences.
Qualifications:
- PhD (2+ years), MS (8+ years), or BS (10+ years) in a scientific discipline (or equivalent).
- Proven ML track record for chemical/biological data, including AI/ML-enabled molecular generation and affinity prediction.
- Experience modeling antibody/antigen sequence, structure, and interactions.
- Proficiency in Python and experience with cloud computing.
- Strong analytical/problem-solving skills; creative and collaborative.
- Ability to explain complex ideas to non-specialists; continuous improvement mindset.
- Learning agility and scientific curiosity; entrepreneurial, strategic problem-solving.
Preferred Qualifications & Skills:
- Experience with modern ML architectures for antibody design (LLMs, diffusion models, flow-matching, Bayesian Optimization, GNNs, etc.).
- Experience designing de novo binders for targets/epitopes.
- Experience analyzing NGS-derived antibody repertoires for sequence- and structure-based design.
- Experience with molecular simulation and conformational analysis.
Benefits (if part of job description):
- Eligible for medical/dental/vision insurance, 401(k) with company match, short-/long-term disability, basic life insurance, tuition reimbursement, paid volunteer time off, company holidays, well-being benefits, up to 80 hours sick time/year, and up to 120 hours paid vacation for new hires (U.S. employees).
- U.S. based employees may be eligible for short-term and/or long-term incentives.
Application Instructions:
- Apply via the “Apply” button.