Position Details:
Our client, a world-leading Pharmaceutical Company in Pearl River, NY is currently looking for an Computational Biologist to join their expanding team.
Job Title: Computational Biologist
Duration: 12 months contract, extendable up to 48 months
Location: Pearl River, NY (Hybrid)
2-3 days/week Onsite
Note:
The client has the right-to-hire you as a permanent employee at any time during or after the end of the contract.
You may participate in the company group medical insurance plan
Job Description:
Education Requirement: Master's degree or Ph.D. in computational biology, bioinformatics, computer science, AI/ML, data science, or a related field
Why Patients Need You
client's purpose is to deliver breakthroughs that change patients' lives. Research and Development is at the heart of fulfilling client's purpose as we work to translate advanced science and technologies into the therapies and vaccines that matter most.
Whether you are in the discovery sciences, ensuring drug safety and efficacy or supporting clinical trials, you will apply cutting edge design and process development capabilities to accelerate and bring the best-in-class medicines to patients around the world.
Position Summary
We are seeking a highly motivated contractor to support vaccine research through computational biology, multi-omics data integration, and AI-enabled research workflows.
The contractor will develop analytical tools and data systems for bulk RNA-seq, single-cell RNA-seq, TCR sequencing, BCR sequencing, and host immune profiling datasets.
The role will also contribute to the design and implementation of an AI-enabled, multi-agent research platform that helps scientists search, integrate, analyze, and reason across complex biological datasets, scientific literature, knowledge graphs, and vaccine research workflows.
Key Responsibilities:
Integrate and analyze multi-omics datasets, including transcriptomics, proteomics, metabolomics, single-cell profiling, and immune repertoire data, to identify biomarkers and molecular signatures relevant to vaccine response, efficacy, and safety.
Demonstrate strong familiarity with state-of-the-art methods and tools for bulk RNA-seq, single-cell RNA-seq, TCR profiling, BCR profiling, and immune profiling data analysis.
Design AI-agent solutions that help researchers explore, query, integrate, analyze, and generate insights from multi-omics datasets and related scientific knowledge.
Build data pipelines and knowledge systems that allow AI agents to retrieve, summarize, connect, and reason across biological datasets, metadata, research workflows, and scientific literature.
Develop interfaces and APIs to support interaction with internal databases, cloud storage, bioinformatics pipelines, and external scientific resources.
Collaborate with computational biologists, data scientists, and software engineers to translate research needs into scalable AI solutions.
Required Qualifications:
Master's degree or Ph.D. in computational biology, bioinformatics, computer science, AI/ML, data science, immunology, or a related quantitative scientific field.
Experience analyzing multi-omics datasets for biomedical or vaccine research, such as genetics, bulk RNA-seq, single-cell RNA-seq, spatial omics, immune repertoire profiling, proteomics, or related data types.
Experience with biomarker discovery, immune-response analysis, or systems immunology, preferably in the context of vaccine, infectious disease, or immunology research.
Strong communication and collaboration skills with the ability to work effectively in a hybrid team environment.
Preferred Qualifications:
Hands-on experience generating immunological insights from single-cell sequencing data is highly desirable.
Expertise in artificial intelligence, large language models, retrieval-augmented generation, agentic AI workflows, or multi-agent system architecture is highly desirable.
Experience building LLM-based applications, multi-agent AI systems, agent orchestration workflows, or autonomous research assistants. Strong software engineering skills in Python and modern AI development frameworks are preferred.
Ability to document code thoroughly to ensure reproducibility and clarity for collaborative projects.
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