Senior Scientist, Bioinformatics / Computational Biology

Are you ready to harness   multi-omics ,   comparative genomics , and   agentic AI   to accelerate vaccines and immune therapies from discovery to the clinic? In this role, you will transform complex human and pathogen datasets into clear, decision-driving insights that shape   antigen design ,   patient stratification , and   translational strategy   across high-priority programs.

Based in   Cambridge , MA you will work in a collaborative, multidisciplinary environment alongside   immunologists ,   molecular biologists , and   data scientists . If you thrive at the intersection of computation and experiment—designing reproducible pipelines on   HPC   and cloud platforms while partnering closely with the lab to iterate rapidly—this role offers the opportunity to influence study design, guide   go/no-go decisions , and help advance novel immune-based therapies toward patients.

Accountabilities

- You will design, implement, and deliver robust analyses across   genomics ,   bulk and single-cell transcriptomics , and   multi-omics   to answer program-critical questions with statistical rigor. You will assemble genomes, call variants, and perform   comparative genomics   and   phylogenetic analyses   on bacterial and viral pathogens to inform antigen selection and surveillance strategy.
- You will apply   machine learning   and statistical modeling to discover biomarkers, stratify patients, predict antigen immunogenicity, and forecast treatment response, translating model outputs into actionable program recommendations. You will also build, optimize, and maintain reproducible workflows using   HPC schedulers   and   AWS   to scale analyses, reduce turnaround time, and ensure traceability.

In addition, you will design and integrate   LLM-powered agentic workflows   for literature mining, data extraction, and pipeline orchestration to accelerate discovery and improve developer productivity. Working closely with experimental scientists, you will propose computationally informed experiments, interpret results, and refine study designs to improve confidence and reduce cycle time.

You will generate translational insights through   differential expression ,   pathway enrichment , and   functional annotation , connecting molecular signals to biological mechanisms and clinical hypotheses. You will produce publication-quality visualizations and reports, present findings clearly to cross-functional stakeholders, and champion   version control ,   workflow managers , and   reproducible research practices   to strengthen code quality and method sharing across programs.

Finally, you will stay current with emerging tools in   bioinformatics ,   AI/ML , and   agentic AI , piloting new approaches, sharing learnings, and scaling successful methods across the portfolio.

Essential Skills and Experience

- You should have a   PhD   in   Bioinformatics ,   Computational Biology ,   Genomics ,   Molecular Biology ,   Computer Science , or a closely related quantitative discipline, with   2 –5 years of industry experience .
- Alternatively, you may have an   MS   in a relevant discipline with   4 –6 years of industry experience   in bioinformatics, computational biology, or genomics.
- A demonstrated track record of independent research through   publications ,   conference presentations , or successful project delivery is expected.
- You should bring proficiency in   R   and/or   Python   for genomic data analysis, statistical computing, and data visualization, including tools such as   ggplot2 ,   Bioconductor ,   tidyverse ,   pandas , and   scikit-learn .
- Hands-on experience with   NGS data analysis   is required, including alignment tools such as   STAR ,   BWA , and   Bowtie2 ; quantification tools such as   Salmon ,   featureCounts , and   HTSeq ; and variant calling tools such as   GATK   and   bcftools .
- You should be familiar with   RNA-seq analysis workflows , including   differential expression   methods such as   DESeq2 ,   edgeR , and   limma , as well as pathway analysis and gene set enrichment approaches such as   ssGSEA   and   MSigDB . Experience working in   Linux/Unix   environments and with   HPC job schedulers   such as   SLURM ,   SGE , or   PBS , and/or cloud computing platforms such as   AWS   or   GCP , is important.

You should also have working knowledge of   Git/GitHub   and reproducible research practices, including   Nextflow   or similar workflow managers. A solid understanding of   molecular biology fundamentals ,   genome annotation , and public bioinformatics databases such as   NCBI ,   Ensembl ,   UniProt , and   PDB   is required, along with foundational knowledge of   machine learning concepts   and applied statistics relevant to biomarker discovery and genomic data.

Success in this role will also require strong analytical thinking, creative problem-solving, and the ability to translate complex datasets into actionable biological insights. You should have excellent written and verbal communication skills, a collaborative mindset, intellectual curiosity, and the ability to manage multiple priorities and deliver results within timelines.

Desirable Skills and Experience

Experience in at least one therapeutic area— infectious diseases ,   oncology , or   inflammatory disease —would be valuable.

We also welcome experience with   comparative genomics   and   microbial or viral genome analysis , including   pangenome methods ,   AMR gene detection , and   phylogenetics .

Additional desirable experience includes building   predictive and prognostic models   using supervised and unsupervised machine learning methods on clinical or preclinical omics data; familiarity with   deep learning frameworks   such as   PyTorch   and   TensorFlow ; and exposure to   biological foundation models   such as   ESM ,   EvolutionaryScale ,   scGPT ,   TranscriptFormer , and   Evo .

We also value experience with or strong interest in   agentic AI workflows   for bioinformatics, including   LLM-orchestrated pipelines ,   retrieval-augmented generation (RAG)   for scientific literature, and tool-using AI agents that interact with databases and analysis tools. Proficiency with AI-assisted coding tools such as   Claude Code   or   GitHub Copilot   is a plus.

Exposure to   single-cell RNA-seq   tools such as   Seurat ,   Scanpy , and   CellRanger ; knowledge of   structural biology tools ,   protein modeling , or   antigen/antibody design ; and experience with   containerization   and   infrastructure-as-code   would also be beneficial. Familiarity with   LLM APIs   and prompt engineering for scientific applications, including structured output generation and multi-agent system design, is also desirable.

Why AstraZeneca

At   AstraZeneca , ambitious science meets everyday collaboration. Here, bioinformaticians, immunologists, clinicians, and engineers come together to share knowledge openly, challenge ideas constructively, and learn from setbacks as they work toward better solutions. You will contribute across diverse therapy areas, with visibility into decisions that matter and support from leaders who encourage experimentation and innovation.

We pair rigorous scientific standards with creativity and value kindness alongside ambition. Most importantly, we connect each individual’s contribution to a clear purpose: translating insights into medicines that can change patients’ lives.

If you are ready to turn   data ,   models , and   modern AI   into faster, smarter decisions for patients, we encourage you to apply and show us how you can make an impact from day one.

The annual base pay for this position ranges from $115,992.00 - $172,671.60. Our positions offer eligibility for various incentives—an opportunity to receive short-term incentive bonuses, equity-based awards for salaried roles and commissions for sales roles. Benefits offered include qualified retirement programs, paid time off (i.e., vacation, holiday, and leaves), as well as health, dental, and vision coverage in accordance with the terms of the applicable plans.

Date Posted
13-Oct-2026

Closing Date
30-Oct-2026
Our mission is to build an inclusive environment where equal employment opportunities are available to all applicants and employees. In furtherance of that mission, we welcome and consider applications from all qualified candidates, regardless of their protected characteristics. If you have a disability or special need that requires accommodation, please complete the corresponding section in the application form.