MULTIPLE POSTDOCS IN LIFELONG MACHINE LEARNING, SERVICE ROBOTICS, AND SOCIAL NETWORK ANALYSIS

The Lifelong Machine Learning group within the General Robotics, Automation, Sensing and Perception (GRASP) Laboratory at the University of Pennsylvania invites applications for multiple full-time postdoc openings on the following topics:
Lifelong Machine Learning (possibly including Deep Learning) - This postdoc will conduct research to develop the next generation of lifelong machine learning algorithms, under funding from DARPA's Lifelong Learning Machines (L2M) program. The postdoc will also collaborate with various other research groups and collaborators on the L2M project. The ideal candidate would have a background in lifelong learning, deep learning, transfer learning, multi-task learning, non-stationary processes, and/or Bayesian methods.
Lifelong Machine Learning and Service Robotics - This postdoc will conduct research on lifelong learning and its application to autonomous mobile service robots that operate continually in university, commercial, and home environments. This postdoc will also work on the DARPA L2M project and collaborate with our team. The ideal candidate would have a background in robotics, lifelong learning, transfer learning, multi-task learning, and/or computer vision/perception. The applicant should be comfortable working with robotic hardware and be experienced in ROS.
Transfer and Multi-Task Learning in Social Network Analysis - This postdoc will work on developing methods for transfer and multi-task learning in large-scale relational data. The ideal candidate would have a background in relational learning, social network analysis, transfer learning, and/or multi-task learning.
In addition to conducting research on the above topics, the Fellows will have opportunities for mentoring students, assisting in the grant proposal process, and broad exposure to other researchers working on these projects.
Applications will be reviewed as they arrive, starting immediately, and will be accepted until the position is filled. For full consideration, we recommend that you apply early.
These positions are available immediately and will be renewable for up to 4 years. A Ph.D. in computer science, machine learning, robotics, physics, or another closely related field is required. The position will report to Dr. Eric Eaton. The compensation package includes a competitive salary, health benefits, career mentoring, and conference travel support.
Candidates should have a strong background in machine learning and/or robotics, supported by a solid publication record in top-tier machine learning, AI, and robotics conferences (e.g., NIPS, ICML, AAAI, IJCAI, IROS, ICRA). Candidates should be familiar with Java, C/C++, and/or Matlab programming in Linux-based environments, and other machine learning (e.g., Tensorflow, Keras, Torch) or robotics toolkits.
To apply, e-mail a single PDF file containing (1) a cover letter, (2) curriculum vitae, (3) research statement, (4) list of representative publications with URLs, and (5) list of references directly to Dr. Eric Eaton (http://www.seas.upenn.edu/~eeaton/) with a subject line of "Postdoc Application: YOUR NAME". Please have 2-3 letters of recommendation sent directly to Dr. Eaton with a subject line of "Postdoc Reference: YOUR NAME".
The University of Pennsylvania is an Equal Opportunity/Affirmative Action Employer. Minority candidates and women are especially encouraged to apply. Hiring is contingent upon eligibility to work in the United States.
For further information, see: http://www.seas.upenn.edu/~eeaton/openpositions.ht...