Computational Biologist and AI Engineer (Vaccines)
SGS Consulting
Job 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.
Skills:
- 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.
- 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.
- Strong communication and collaboration skills with the ability to work effectively in a hybrid team environment.
Education/Experience:
- Master’s degree or Ph.D. in computational biology, bioinformatics, computer science, AI/ML, data science, immunology, or a related quantitative scientific field.
Vacancy posted 3 days ago
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