Senior Computational Scientist

Twist Bioscience•South San Francisco, CA

3d•$150,700 - $180,800

About The Position

Twist is seeking a Senior or Staff Computational Scientist to develop AI and computational solutions for protein design, discovery, and characterization. You will work across computational biology, machine learning, and experimental science, collaborating with research scientists, software engineers, and customer-facing teams. Your work will help Twist and its customers design and evaluate protein sequences, interpret NGS and experimental data, and select candidates for advancement. This is a hands-on, impact-driven role requiring substantial experience developing new algorithms. A strong understanding of protein language models (PLMs) and their use in biological sequence design is required. Experience with antibody discovery or engineering is highly preferred but not required. Candidates with relevant experience in other therapeutic proteins are encouraged to apply.

Requirements

Minimum of 5 years of industry experience with a PhD.
PhD in computational biology, bioinformatics, machine learning, computer science, protein science, or a related field.
Extensive experience developing algorithms for protein design, engineering, discovery, or sequence analysis.
Demonstrated experience developing and applying AI/ML methods to proteins or other biological sequences.
Strong understanding of protein language models (PLMs) and protein sequence-structure-function relationships.
Experience analyzing NGS data from biological selection, screening, or related workflows.
Strong scientific programming skills (Python) and experience with modern machine-learning frameworks (PyTorch, TensorFlow).
A record of translating ambiguous scientific questions into validated computational methods and actionable results.
Strong cross-functional communication skills, scientific judgment, and a focus on practical impact.
Ability to communicate complex computational concepts to experimentalists and stakeholders.

Nice To Haves

Experience with antibody discovery, engineering, or characterization is highly preferred but not required.
Experience with biopanning, display-based discovery, or other protein-selection platforms.
Experience integrating protein sequence, NGS, and experimental assay data.
Experience with generative protein design, property prediction, or candidate-ranking methods.

Responsibilities

Develop algorithms that integrate protein sequences with NGS and experimental data to derive insights that inform subsequent experiments and design cycles.
Identify high-impact opportunities for new algorithms and AI-enabled capabilities, lead their development from concept through experimental validation, and translate successful approaches into reusable tools for research programs.
Develop AI/ML methods for designing, evaluating, and optimizing therapeutic protein sequences.
Apply protein language models (PLMs) and related approaches to sequence generation, property prediction, and candidate prioritization.
Partner with software and bioinformatics teams to integrate models and analytical workflows into scalable research systems.
Lead computational analyses for protein discovery programs, including sequence selection, clone prioritization, and characterization.
Collaborate across computational, experimental, engineering, and customer-facing teams to translate scientific needs into practical solutions.
Move flexibly between research, software development, analysis, and troubleshooting as program priorities evolve.