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Postdoc openings in Reinforcement Learning for Robotics

davsca – Posted on April 12, 2017 at 2:55 pm –


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Job Description

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Our vision is to make drones one day able to navigate as birds or better than birds, using mainly onboard vision sensors. To achieve this goal we investigate how machine learning, novel sensors (such as event cameras), and coupled perception and control can be used to advance the state of the art. We are looking for motivated researchers to help make this vision a reality!

The postdoctoral researcher in Reinforcement Learning for Robotics will develop models that allow an artificial agent to interact with its environment, in order to achieve some complex tasks. At the same time, the agent should learn how to cope with high variability in environmental conditions. These models will be built and tested both on real world and simulated environments. The main application domains will micro flying robots.

An up-to-date list of our current research projects is here. For videos, please check out our YouTube channel.

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Benefits

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The position is fully funded. PhD student and Postdoc positions in Switzerland are regular jobs with social benefits (i.e., a pension plan!). You will get a very competitive salary and access to excellent research facilities (motion capture, 3D printing, a large flying arena, electronic and machine workshops). Zurich is regularly ranked among the top cities in the world for quality of life. Additionally, we have a very enjoyable work atmosphere and organize many social events, such as ski trips, hikes, dinners, and lab retreats.

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Who we are

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We are a research lab of the Computer Science Department of the University of Zurich. As of August 2017, our lab will be affiliated with the Institute of Neuroinformatics of the University of Zurich and ETH Zurich. The lab was founded in 2012 and has made world-class contributions in visual SLAM, event-based vision, and vision-based navigation of quadrotors, which resulted in many prestigious awards, research grants, and media coverage . Our lab has been many times in the in the spotlight of the international press . More recently, we were on many news worldwide for our works on deep learning for autonomous forest trail following and agile navigation of quadrotors using standard cameras or event based cameras.

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Your Skills

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  • A passion for computer vision, robotics, mathematics, programming and abstract thinking
  • A PhD degree in computer engineering, computer science, robotics, or related fields
  • Excellent track record (publications in high-impact-factor conferences and journals)
  • Excellent written and spoken English skills
  • In addition, you should meet the following requirements:

    • Proven theoretical and practical experience in solving large-scale reinforcement-learning problems.
    • Ability to develop and implement complex algorithms efficiently
Recommended: Strong experience with C++, Python, Deep Learning frameworks, GPU optimization skills. Familiarity with tools such as ROS, TensorFlow, OpenCV, and Git is desirable.
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How to apply
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APPLY HERE

You will be requested to upload single PDF including (in the order):

  • 1. Letter of motivation (max half page). Please specify your strong experience in “Reinforcement Learning” or “Deep Learning for Computer Vision problems”. Please show evidence with publications in strong venues.
  • 2. Your CV (please include: your Nationality for visa requirements, Date of Birth, your English level, scientific publications, hobbies). Please include the publication list and reprints of your 3 major publications;
  • 3. List of at least 3 referees (support-letter writers). Support letters will be requested only if your application is considered. So you don’t need to upload them now.
  • .

Please include your homepage and link to videos if available. The letter of motivation should comment on the required skills mentioned in the bullet point list above.

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Contact

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For questions, please contact Prof. Davide Scaramuzza at: careersrpg (AT) ifi (DOT) uzh (DOT) ch (please do not use his private email for inquiries about these job positions). Applications sent directly by email and not through the web form will not be considered. In case of positive feedback, you will be contacted within 4 weeks from your application. If not positive, you won’t hear back.


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