Pattern Agentix
https://www.patternagentix.comAbout
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Jobs at Pattern Agentix
We are seeking a Bioinformatician with a strong background in genomics and transcriptomics, and proven experience with biological ontologies. The successful candidate will analyze outputs from pre-processed biological pipelines and support their integration into a biomedical knowledge graph.
Responsibilities:
Review and interpret genomics and transcriptomics datasets from existing pipelines
Leverage biological ontologies (e.g., GO, DO, HPO) to structure and standardize biological entities
Assist in designing and building components of a biological knowledge graph
Collaborate with computational biologists, data scientists, and software engineers
Document processes and contribute to reproducibility and data governance standards
Qualifications:
MSc or PhD in Bioinformatics, Computational Biology, or a related field
Strong knowledge of genomics and transcriptomics workflows
Experience working with biological ontologies and controlled vocabularies
Familiarity with RDF, OWL, or other semantic web technologies is a plus
Proficiency in Python, R, or similar data analysis tools
Excellent analytical and communication skills
Preferred Experience:
Previous work with knowledge graphs or biomedical data integration
Pattern Agentix is seeking a skilled engineer to design and develop a comprehensive knowledge graph that spans multiple biological domains—including molecular biology, biochemistry, biophysics, immunology, virology, pharmacology, and computational biology. The goal is to integrate heterogeneous datasets (ontologies, public databases, scientific literature) into a scalable, semantically rich graph that supports hypothesis generation and interdisciplinary research.
Responsibilities:
• Architecture & Design:
- Develop a scalable knowledge graph architecture using graph databases (e.g., Neo4j, ).
- Design data models to capture entities (e.g., genes, proteins, chemical compounds, immune markers) and their relationships.
• Data Integration & Curation:
- Integrate data from domain-specific ontologies (e.g., Gene Ontology, ChEBI) and public repositories (e.g., UniProt, PDB).
- Build API connectors and automation pipelines for data ingestion.
- Leverage NLP tools to extract relationships from scientific literature with validation by domain experts.
• Collaboration & Documentation:
- Work closely with interdisciplinary teams and domain experts to ensure semantic accuracy.
- Document data models, integration methods, and curation guidelines.
Requirements:
• Proven experience in knowledge graph development and graph databases (Neo4j, GraphDB, etc.).
• Strong programming skills (Python, Java, or similar) and experience with API development.
• Familiarity with semantic web technologies (RDF, ) and ontology management tools
• Solid background in bioinformatics, computational biology, or related disciplines.
• Demonstrated ability to work with heterogeneous data sources and interdisciplinary projects.
Contract
We are seeking part time or full time on contract and will compensate to local norms.
Machine Learning (ML)
Data SciencePattern Agentix (patternagentix.com) is seeking a Graduate AI researcher and developer to create advanced multi-agent AI systems leveraging cutting-edge AI research and Retrieval-Augmented Generation (RAG) techniques. The ideal candidate should have a strong academic and research background in AI, demonstrated through published research papers, open-source contributions (e.g., GitHub).
Exposure to bioinformatics or some background in bioinformatics a plus.
Key Responsibilities
Conduct advanced AI research and apply findings to develop scalable multi-agent AI architectures.
Develop intelligent AI agents using modern frameworks
Apply Retrieval-Augmented Generation (RAG) techniques to enhance agent capabilities.
Required Skills & Experience
Master’s or Ph.D. in AI, Machine Learning, Computer Science, or a related field with some exposure to bioinformatics.
Strong AI research background, demonstrated through peer-reviewed publications in top-tier AI/ML conferences or journals (e.g., NeurIPS, ICML, AAAI, CVPR, ACL, etc.).
Proficiency in Python and experience with AI/ML frameworks (e.g., PyTorch, TensorFlow).
Experience with multi-agent AI systems and their architectural design.
Project Scope
The project involves developing a sophisticated multi-agent system that:
Leverages RAG for improved information retrieval and knowledge generation.
We are open on compensation models but compensation will be aligned to local norms. We would consider part time or full time.
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