Senior Staff Bioinformatics Scientist (AI-guided protein engineering)

ILLUMINA CAMBRIDGE LIMITED Singapore Branch; Singapore; Presencial; SGD 180.000 - 240.000; Jornada completa

Descripción de la vacante

Illumina Cambridge Limited Singapore Branch seeks a Senior Staff Scientist to build data foundations for protein engineering and connect sequence, structure, and assay data to AI/ML models. You will lead method development, evaluate design-build-test-learn workflows, and define how screening results become reusable data assets.

The role requires senior technical leadership across computational biology, AI/ML, automation, and experimental execution in a fast-growing environment.

Formación

• Ph.D. in computational biology or related fields or equivalent experience.
• Demonstrated ability to lead computational biology or protein engineering projects.
• Experience applying AI/ML to protein design and screening analytics.
• Experience designing reproducible data infrastructures for analytics.
• Strong programming skills (Python, C/C++, R) and statistical modeling.

Responsabilidades

• Build reusable data foundations for protein engineering workflows.
• Develop computational workflows linking sequence, structure, and assay data to AI/ML models.
• Benchmark internal and external computational methods for enzyme design.
• Deliver reusable scripts, dashboards and pipelines for teams.
• Advance semi-closed-loop and closed-loop DBTL design-build-test-learn systems.
• Collaborate with cross-functional teams across global programs.

Conocimientos

Computational biology leadership

AI/ML in protein design

Screening analytics

Data infrastructure

Wet-lab HT screening

Programming: Python

Programming: C/C++

Statistics

Communication

Educación

Ph.D. in computational biology

Descripción del empleo

Why us

Illumina is the global leader in Next Generation Sequencing (NGS) technology. Through relentless innovation, Illumina has reduced the cost of sequencing a human genome from hundreds of thousands of dollars to below $200. The drastic cost reduction has moved NGS from the laboratory to the clinic, with wide-ranging impact from cancer diagnostics to genetic testing. We invite you to join us in our effort to improve human health by unlocking the power of the genome.

Position summary

We are seeking a Senior Staff Scientist to help build computational tools and data foundation for our protein engineering group across global enzyme engineering programs. This role will connect data structures for high-throughput and mid-throughput screening, participate in method development and evaluation, and help establish semi-closed-loop and closed-loop design-build-test-learn workflows.

The successful candidate will provide senior technical leadership at the interface of protein engineering, AI/ML design, screening data systems, automation, and experimental execution. This scientist will define how screening results become reusable data assets as well as how computational methods are benchmarked and adopted.

The role is based in Singapore. This is an exciting opportunity to be a part of Illumina's continued growth.

Responsibilities include, but are not limited to:

• Build reusable data foundations for protein engineering. Define data structures, metadata standards, variant lineage, assay context, controls, replicate handling, uncertainty, and negative data capture across high- and mid-throughput screening workflows.


• Enable model-guided enzyme engineering. Develop and evaluate computational workflows that connect sequence, structure, assay, and screening datasets to AI/ML models, design rationale, variant prioritization, and next-round library design.


• Benchmark computational and AI methods. Assess internal pipelines, open-source methods, commercial protein design platforms, and emerging scientific agents using retrospective and prospective performance metrics relevant to enzyme engineering programs.


• Deliver practical tools for project teams. Create reusable scripts, templates, dashboards, lightweight applications, and analysis pipelines that help experimental and computational teams run routine analyses and interpret recommendations efficiently.


• Advance closed-loop DBTL workflows. Help establish semi-closed-loop and closed-loop design-build-test-learn systems in which experimental results are captured, analyzed, modeled, reviewed, and converted into actionable design recommendations.


• Partner across global engineering programs. Work closely with experimental scientists, automation teams, informatics, software engineering, data engineering, chemists, biophysicists, and platform teams to ensure computational workflows align with assay throughput, operational constraints, and program goals.


• All listed tasks and responsibilities are deemed as essential functions to this position; however, business conditions may require reasonable accommodations for additional task and responsibilities.

Education, Experience & Attributes required

• Ph.D. in computational chemistry, computational biology, bioinformatics, computer science or related fields, or equivalent work & educational experience.


• Significant experience leading computational biology, protein engineering, AI/ML, screening analytics, or scientific data infrastructure efforts


• Deep experience applying computational or data-driven methods to protein engineering, enzyme engineering, directed evolution, assay analysis, or related biological design problems.


• Demonstrated ability to design data structures or analytical systems that support reproducible analysis, model training, and cross-project learning.


• Wet-lab experience in high-throughput or mid-throughput screening and/or biochemical assay designs.


• Solid programming skills in at least one of the major programming languages (e.g., C/C++, Python, R).


• In-depth knowledge of protein sequence or structure modelling, protein-ligand interaction predictions and/or molecular simulations.


• Understanding of AI/ML methods and practical experience in adopting AI/ML-driven protein-design models.


• Strong fundamentals in statistical modelling, algorithm design, data analysis, and/or visualization methods.


• Excellent verbal and written communication skills.


• Collaborative, open and self-aware, team player, and able to rapidly integrate into cross functional teams.


• Highly motivated individual with proven ability in thinking innovatively and the proven track record of productive research and development.


• Strong applicants with lesser experience will be considered for a position commensurate with the experience.

Preferred experiences and attributes

• Experience with foundational AI/ML models and protein language models for protein engineering, including generative protein design, zero-shot variant scor