Four funded undergraduate research assistant position for Fall 2020 [closed]

UMass Lowell incoming freshmen who are awarded merit scholarships through the early action admission process (award for $4,000) are eligible to apply for a research assistant position in our research lab.

Supervisor: Prof. Reza Ahmadzadeh

Research topics include but not limited to: Robot Learning, Reinforcement Learning, Imitation Learning, Learning from Demonstration, and beyond.

Mission of the lab

The mission of our lab, PeARL (Persistent Autonomy and Robot Learning Lab) is to develop novel robot learning algorithms that will allow robotic platforms to interact with humans effortlessly, learn new skills autonomously, and generalize their capabilities robustly in dynamic environments. To achieve these goals, we investigate how machine learning, AI, and novel sensors/hardware can be used to advance the state of the art of robot learning and to improve robots' level of autonomy. Our research is carried out on manipulators, mobile robots, and mobile manipulation platforms. We are looking for motivated researchers to help make this vision a reality!

Job Description

You will work on novel robot learning algorithms that combine model-based and machine learning methods (both Imitation Learning and/or (Inverse) Reinforcement Learning) to accomplish effortless physical human-robot interaction or persistent autonomy in dynamic and harsh environments. The algorithms can be designed for fixed manipulator arms and/or mobile manipulator platforms, as well as walking robots.

To see the specific project description, please log onto the Jobhawk website.

Benefits

The successful candidate will have access to the PeARL lab (Persistent Autonomy and Robot Learning Lab) and several robotic platforms including manipulator, mobile, walking, and mobile manipulator robots.

Your Skills

• A passion for robotics, modeling, mathematics, programming and abstract thinking

• Excellent written and spoken English skills

• A background in Linear Algebra, Calculus, Probability and Statistics, and Algorithms

• (Preferable) Good programming skills in Python, C++, and/or MATLAB

• (Plus) Familiarity with tools such as ROS, Gazebo, MoveIt, YARP, Tensorflow, Pytorch, and OpenCV

Start Date

The student can select to work either during the academic year or summer. Moe information can be found in the job description.

To Apply

Log onto the Jobhawk website and follow the instructions.

Get in touch if you have any further questions.

reza@cs.uml.edu