This Associate Principal Scientist role drives proprietary data generation to build the world's largest human cardiac tissue multiomics dataset. You will design protocols for human tissue processing, manage partnerships with hospitals and academics, and coordinate data integration into multiomic models. This is a unique opportunity to contribute to the discovery and development of cardiovascular therapies with real, lasting impact.
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Associate Principal Scientist Multiomic Data Generation at AI-driven biotech drug discovery
Are you a PhD-level scientist passionate about groundbreaking drug discovery? Join a pioneering biotech platform leveraging human heart multiomics data and computational modeling to uncover first-in-class cardiovascular therapies. This Associate Principal Scientist role offers a unique chance to build the world's largest proprietary human cardiac tissue multiomics dataset, driving real, lasting impact in a well-funded, innovative environment.
Overview
Role overview
Company
About the company
AI-driven biotech drug discovery platform
Responsibilities
What you will do
- Design and implement protocols for the procurement and processing of human tissue samples for multiomics data.
- Manage and coordinate relationships with a network of hospitals, academics, and contract research organisations.
- Support in driving the proprietary data generation strategy and coordinate data integration into multiomic models.
Candidate profile
Who this is a fit for
- PhD level scientist with relevant experience in handling human tissue samples and generating omics data.
- Demonstrable experience in designing and managing multiomics data generation projects.
- Strong understanding of technology analysis pipelines for multiomics data.
What makes it remarkable
Why this role is remarkable
- Contribute to building the world’s largest proprietary human cardiac tissue multiomics dataset.
- Drive the discovery and development of cardiovascular therapies with real, lasting impact.
- Join a dynamic team leveraging cutting-edge computational modeling and a global network for groundbreaking innovation.
Meet Jack
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