
Posted 14 hours ago
Research Assistant
Ellison Institute of TechnologyResearch Assistant (Jamali Lab) - Generative Biology Institute
Perks & benefits
Education AllowancePaid Leave
Requirements
Bachelor's degree in Biology, Chemistry, Engineering, or Computer Science, Previous research laboratory experience, Strong organizational and communication skills
Skills
Synthetic BiologyProtein DesignComputational Biology
About the role
About the Company
At the Ellison Institute of Technology (EIT), we’re on a mission to translate scientific discovery into real world impact. We bring together visionary scientists, technologists, engineers, researchers, educators and innovators to tackle humanity’s greatest challenges in four transformative areas: Health, Medical Science & Generative Biology; Food Security & Sustainable Agriculture; Climate Change & Managing CO₂; and Artificial Intelligence & Robotics.
Responsibilities
- Assist in scientific studies and experiments by collecting and analysing data under the guidance of senior scientists
- Perform routine laboratory tasks such as preparing samples, setting up equipment, and maintaining lab safety protocols
- Analyse experimental data using software tools and prepare reports and presentations
- Support the Research Group in the development of written materials, including publications and protocols
- Carry out desk-based research to establish the state of the art in scientific areas related to GBI
- Stay current on scientific advancements in synthetic biology through journals and conferences
- Provide general day to day support to the wider team
Requirements
- Bachelor's degree in Biology, Chemistry, Engineering, or Computer Science
- Previous experience working in a research laboratory
- Ability to work effectively in a high-growth, fast-paced environment
- Highly organised with ability to manage multiple projects
- Excellent oral and written communication skills
- Experience with problem solving involving multiple stakeholders
Preferred Qualifications
- Interest in developing computational methods for the design of conformationally dynamic and functional enzymes
- Experience with generative protein design models
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Ellison Institute of Technology · Oxford
