Remote Part-Time Computational Biologist (AI/ML)

The Emmes Company, LLC; Rockville (MD); Remote; USD 55,000 - 96,000; Part time

Job summary

Essex Management, an Emmes Company, seeks a Computational Biologist (AI/ML) to apply advanced AI methods to biomedical datasets in a part-time, US-remote capacity. The role focuses on integrating AI/ML techniques across genomic, proteomic, and clinical data to support translational research and precision medicine.

The candidate will design, test, and optimize AI/ML pipelines, leverage LLMs and RAG for data interoperability, and deliver interpretable reports to stakeholders.

Qualifications

• Bachelor's or advanced degree in bioinformatics or closely related field.
• 2–5 years of relevant professional or research experience.
• Experience applying AI/ML to biomedical or multi-modal datasets.
• Experience with LLMs or RAG approaches preferred.
• Ability to communicate complex results to diverse audiences.

Responsibilities

• Design and implement AI/ML models applied to biomedical data, including genomic, proteomic, and multimodal clinical datasets.
• Apply large language models, retrieval-augmented generation (RAG) techniques, and graph neural networks to biomedical data.
• Develop, test, and optimize pipelines for variant calling and annotation leveraging modern ML workflows and frameworks.
• Curate, model, and integrate genetic and clinical datasets into standardized, interoperable formats.
• Generate high-quality, interpretable reports for internal and external stakeholders.

Skills

Python

SQL

ML frameworks

Git

LLMs / RAG

Genetic variant standards

Cross-functional communication

Education

Bachelor's degree or advanced degree in bioinformatics, computational biology, data science, genetics, biology, health informatics, clinical research, or related field

Tools

HGVS

VCF

Job description

Essex Management, an Emmes Company, seeks a Computational Biologist (AI/ML) to apply advanced AI methods to biomedical datasets in a part-time, US-remote capacity. The role focuses on integrating AI/ML techniques across genomic, proteomic, and clinical data to support translational research and precision medicine.

The candidate will design, test, and optimize AI/ML pipelines, leverage LLMs and RAG for data interoperability, and deliver interpretable reports to stakeholders.