Rare Disease Translational Research Associate

Maine Tech Hub; Bar Harbor (ME); On-site; USD 43,000 - 72,000; Full time

Job summary

The Jackson Laboratory in Bar Harbor, ME is seeking a full-time Research Assistant to join the Rare Disease Translational Center. You will help characterize disease progression in mouse models, perform tissue collection, histology, and molecular assays, and generate high-quality data for preclinical studies.

This role offers hands-on lab work with opportunities to advance skills in molecular biology, phenotyping, and omics approaches, supporting translational decisions within a collaborative

Qualifications

• Bachelor's degree required.
• 2+ years hands-on lab experience preferred.
• Experience with molecular biology workflows beneficial.

Responsibilities

• Troubleshoots research procedures and refines methods as needed.
• Maintains research documentation and updates methodologies.
• Manages lab resources and coordinates workspace.
• Shares procedures with and trains team members.
• Performs assigned tasks using established methods and data tools.
• Organizes, analyzes, and summarizes research data.
• Contributes to manuscripts, reports, and grant materials.
• Conducts multiple experiments and maintains equipment.
• Demonstrates mouse handling and husbandry skills.

Skills

Mouse handling

Protocol development

Project coordination

Lab safety

Data analysis

Presentation skills

Communication

Time management

Team player

Flexibility

Education

Bachelor's degree

2+ years lab experience

Molecular biology basics

Tools

Histology

RNA-seq & proteomics

Job description

The Jackson Laboratory in Bar Harbor, ME is seeking a full-time Research Assistant to join the Rare Disease Translational Center. You will help characterize disease progression in mouse models, perform tissue collection, histology, and molecular assays, and generate high-quality data for preclinical studies.

This role offers hands-on lab work with opportunities to advance skills in molecular biology, phenotyping, and omics approaches, supporting translational decisions within a collaborative