We are accepting applications for an open Post-Doc position in Deep Bayesian Robotics at ShanghaiTech University. This position is for an ongoing project which aims to teach robots to behave in our environment and to adapt their behavior to malfunctions/disturbances. Although the chosen tools and approaches are still flexible, we put a strong emphasis on research focused on 1. Parametric search with Bayesian Optimization, 2. Deep Bayesian Learning applied to Policy-search algorithms or 3. Model Predictive Control. For information about this vacancy, you can contact Andre Rosendo, Assistant Professor, email: arosendo@shanghaitech.edu.cn<mailto:arosendo@shanghaitech.edu.cn>.
崗位名稱： Post-Doc position
崗位人數(shù):1
Research focused on 1. Parametric search with Bayesian Optimization, 2. Deep Bayesian Learning applied to Policy-search algorithms or 3. Model Predictive Control. We are looking to appoint skilled and enthusiastic engineers with programming experience (or a good mathematical foundation) and strong interest in experimenting with robots, and we have two generous funds to be used to buy whatever robot necessary for your research. You will be expected to work side-by-side with English-speaking graduate students at the Living Machines Laboratory, to read recent papers while implementing state-of-the-art algorithms, to comprehend and improve this state-of-the-art and, more importantly, conduct experiments to validate theories and algorithms.
1. a PhD in robotics, computer science, mechatronics, mechanical engineering or related field by the start date
2. demonstrate interest in Reinforcement Learning algorithms and other learning/control methods
3. desirable experience modeling robots using a physics-engine/multibody dynamics simulator
4. proficiency in C++ or Python programming and experience developing real-time applications
5. excellent written and verbal English communication skills
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