Conduct research focused on designing and implementing algorithms related to cryo-electron microscopy (cryo-EM) data collection in a lab that focuses on the structural biology and biophysics underlying microtubule-based intracellular transport. Advise on cryo-EM algorithms and associated mathematical underpinnings in data processing. Utilize a combination of reinforcement learning, path planning, and Bayesian optimization. Plan and perform experiments, oversee research performed by students and research technicians, and mentor and train postdoctoral fellows, graduate students, and undergraduates. Write grant applications and scientific manuscripts for submission to computer science conferences and journals.

Requires PhD degree in Electrical Engineering, Computer Science or related + 2 years of experience researching multi-armed bandit problems and developing and analyzing Bayesian optimization and reinforcement learning algorithms + at least 3 first author peer-reviewed articles focused on mathematical modeling and solving online decision-making problems in the face of uncertainty.

Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes.

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All applications for this position must be received by 11:59p Thursday, June 19th.

The University of Michigan is an equal employment opportunity employer.