Remote AI/ML Computational Biologist (Biomed)

Emmes Group; Rockville (MD); Remoto; USD 83.000 - 131.000; Part-time

Descrizione del lavoro

Essex Management, part of Emmes Group, seeks a Computational Biologist (AI/ML) to design and deliver AI-driven bioinformatic analyses for federal programs. You will apply AI/ML and deep learning to genomic, proteomic, and multimodal clinical data within precision oncology and translational research.

Own defined tasks, contribute to method discussions, and develop interoperable pipelines using RAG/LLMs with a focus on high-quality scientific outputs for internal and external stakeholders.

Competenze

• Bachelor's degree or higher in bioinformatics, computational biology, data science, genetics, biology, health informatics, or a related field.
• 2 to 5 years of relevant professional or research experience.
• Demonstrated success applying AI/ML to biomedical or multi-modal datasets (genomics, proteomics, clinical).
• Track record of publications or applied innovation in AI-driven data science for life sciences preferred.

Mansioni

• Design and implement AI/ML models applied to biomedical data to support precision oncology and translational research.
• 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.
• Curate, model, and integrate genetic and clinical datasets into standardized, interoperable formats.
• Generate high-quality, interpretable reports for internal and external stakeholders.

Conoscenze

Python

SQL

PyTorch

TensorFlow

GNNs

HGVS/VCF

LLMs/RAG

Git

Formazione

Bachelor's or higher in bioinformatics, computational biology, data science, genetics, biology, health informatics

Descrizione del lavoro

Essex Management, part of Emmes Group, seeks a Computational Biologist (AI/ML) to design and deliver AI-driven bioinformatic analyses for federal programs. You will apply AI/ML and deep learning to genomic, proteomic, and multimodal clinical data within precision oncology and translational research.

Own defined tasks, contribute to method discussions, and develop interoperable pipelines using RAG/LLMs with a focus on high-quality scientific outputs for internal and external stakeholders.