Research Associate I - College of Engineering - Biomedical Engineering

Carnegie Mellon University is a private, global research university that stands among the world’s most renowned education institutions. With ground-breaking brain science, path-breaking performances, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it.

The Biomedical Engineering (BME) Department at Carnegie Mellon University is renowned for its interdisciplinary approach to solving complex healthcare challenges. The Engineered Morphogenesis Group is part of the Department of Biomedical Engineering at Carnegie Mellon University (CMU) on the Pittsburgh campus. We aim to develop next-generation theragnostic technologies and treatments for genetic and environmentally induced pathologies. Our research probes the interplay between stem cells and (patho)physiology through the engineering of organoids for biorobotic and pharmaceutical applications.

We are seeking a Laboratory Automation Engineer (Part-Time / Intern, 20 hours/week anticipated) to help devise, trial, and test new automated workflows in CMU’s Biological & Chemical Innovation Cloud Lab (Cloud Lab) to support increased throughput in cell and organoid culture.

Core Responsibilities:

Cell & Organoid Engineering:

• Learn the fundamentals of cell and organoid culture, achieving proficiency as monitored by supervisors.
• Become familiar with existing experimental workflows.

Automation, Testing, & Analysis:

• Learn and use automation technologies available in the Cloud Lab, including both hardware and software systems.
• Integrate automation technologies into existing workflows with an emphasis on throughput and reproducibility.
• Synthesize and analyze data generated from automated experiments to inform iterative workflow improvement.

Collaboration:

• Work closely with cell culture teams to develop and integrate automated workflows.
• Regularly participate in and present during group meetings, covering project overviews, results, and future goals.

Qualifications:

• Currently pursuing or recently completed a MS degree in Computer Science, Biomedical Engineering, Mechanical Engineering, or a related field. Outstanding recent BS graduates will also be considered.
• Proficiency in constructing machine learning models for describing and predicting experimental outcomes.
• Prior experience in laboratory automation for life sciences is highly desirable.
• Prior experience with cell and tissue culture is desirable but not required.
• Ability to work onsite in Pittsburgh, PA.

A combination of education and relevant experience from which comparable knowledge is demonstrated may be considered.

Requirements: Successful Background check