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Harvard University Postdoctoral Fellow in Resilient Multi-Robot Systems in Cambridge, Massachusetts

Details

Title Postdoctoral Fellow in Resilient Multi-Robot Systems

School Harvard John A. Paulson School of Engineering and Applied Sciences

Department/Area Computer Science

Position Description

Postdoctoral fellow will conduct research in multi-agent coordination with a particular focus on cases where malicious agents in the network disrupt optimal or nominal coordination between agents. We are interested in developing the theory and accompanying analysis to characterize and mitigate the impact of adversarial agents on multi-agent coordination schemes. Some particular areas of interest are consensus systems, distributed optimization (and federated learning), and game theory. Postdoctoral fellow will be expected to publish results in top tier control and robotics journals (such as but not limited to, Transactions on Automatic Control, Automatica, Transactions on Robotics, International Journal on Robotics Research, and Science Robotics), mentor and collaborate with PhD students in the lab, and contribute to related research proposals. Developed algorithms and derived results may be deployed and validated on actual multi-robot system platforms in the REACT Lab.

Basic Qualifications

Doctorate degree in related engineering and mathematical fields including Operations Research, Electrical Engineering, Applied Math, CS, by the time the appointment begins.

Additional Qualifications

Strong publication record in a related field, evidence of mathematical rigor, prior experience with optimization, control, game theory, commitment to performing high quality research, and interest in leadership and ideation process.

Special Instructions

CV, transcript, sample of relevant publications, references

Contact Information

Sarah Gayer

Contact Email sgayer@g.harvard.edu

Equal Opportunity Employer

Harvard is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, sex, gender identity, sexual orientation, religion, creed, national origin, ancestry, age, protected veteran status, disability, genetic information, military service, pregnancy and pregnancy-related conditions, or other protected status.

Minimum Number of References Required 3

Maximum Number of References Allowed 3

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