Remote AI/ML Computational Biologist

The Emmes Company, LLC; Rockville (MD); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Flexible Approved Time Off

Tuition Reimbursement

401k Retirement Plan

Work From Home Anywhere in the US

Maternal/Paternal Leave

Casual Dress Code & Work Environment

Job summary

The Emmes Company, LLC is seeking a Computational Biologist (AI/ML) within the Bioinformatics Department of the BIDS Division at Essex. This role focuses on applying AI, ML and Deep Learning to biomedical data, with ownership of well-defined tasks and small projects in a fast-paced, collaborative environment.

Responsibilities include designing and implementing AI/ML models for genomic, proteomic and multimodal datasets, leveraging LLMs, RAG, and graph neural networks, and delivering high-quality

Qualifications

• Bachelor's degree or advanced degree in bioinformatics, computational biology, data science, or a related field.
• 2 to 5 years of relevant professional or research experience.
• Experience applying AI/ML to biomedical data preferred.

Responsibilities

• Own and execute analytical tasks and small projects with minimal supervision.
• Assist Associate Informaticists with task-related questions and troubleshooting.
• Contribute to team discussions on methodology, standards, tools, and technical decisions.
• Design and implement AI/ML models for biomedical data to support precision oncology and translational research.

Skills

Python

SQL

ML frameworks

Git

Communication

Education

Bachelor's in bioinformatics

Tools

PyTorch

TensorFlow

R

Job description

The Emmes Company, LLC is seeking a Computational Biologist (AI/ML) within the Bioinformatics Department of the BIDS Division at Essex. This role focuses on applying AI, ML and Deep Learning to biomedical data, with ownership of well-defined tasks and small projects in a fast-paced, collaborative environment.

Responsibilities include designing and implementing AI/ML models for genomic, proteomic and multimodal datasets, leveraging LLMs, RAG, and graph neural networks, and delivering high-quality