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. If you’re passionate about joining a community that challenges the curious to deliver work that matters, your journey starts here! The Biomedical Engineering (BME) Department at Carnegie Mellon University is renowned for its interdisciplinary approach to solving complex healthcare challenges. Located within CMU's College of Engineering, the department emphasizes the integration of engineering principles with biomedical sciences to address pressing medical and biological issues. The department is characterized by its focus on creating impactful technologies and therapies that improve patient care and advance biomedical innovation globally. 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 (three-dimensional mini [... source excerpt omitted ...] r engineers who enjoy problem-solving and hands-on experimentation, have strong attention to detail, and value developing technologies with tangible real-world applications. 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 aut [... source excerpt omitted ...] ternal and external partners at a high level of integrity. We are looking for someone who shares our values and who will support the mission of the university through their work. 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 Pitts