JOB POSTING INFORMATION
Position Type:	Professional Experience Year Co-op (PEY Co-op: 12-16 months)
Job Title:	Robotic Research Internship at the TUM Learning Systems and Robotics Lab (Prof. Angela Schoellig)
Job Location:	Munich, Germany (Preferred) or Toronto, Canada
Job Location Type:	On-Site
If working on site, can you provide a copy of your COVID-19 safety protocols?:	Yes
Number of Positions:	2
Salary:	$0.00 hourly for 0.0 hours per week
Start Date:	05/01/2024
End Date:	04/30/2025
Job Function:	Robotics Research and Software Engineering
Job Description:	Being a part of the TUM Learning Systems and Robotics Lab (www.learnsyslab.org), led by Prof. Angela Schoellig, you will have the chance to engage in cutting-edge research at the intersection of robotics, machine learning, and system control. Our research is motivated by the vision of a seamless interaction of robotic systems with the physical world. In particular, our research interests are centred around the challenges associated with robots operating in increasingly unstructured, uncertain and changing environments and over long periods of time. These situations challenge current robot designs, which rely on knowing the specifics of the environment and tasks ahead of time in order to operate safely and efficiently. As a research intern, you will work in collaboration with graduate students and senior researchers within the lab and develop innovative solutions to push the boundaries of state-of-the-art robot perception and decision-making algorithms. We offer opportunities for you to sharpen both soft and technical skills through the course of the internship.   * Technical areas: Control theory, reinforcement learning, robot simulation, and real-world robotics experimentation  * Software toolboxes: Python, C++, Robot Operating System (ROS), CasADI, OpenAI Gym, PyTorch, and PyBullet  * Transferrable skills: Conduct thorough literature reviews to understand the current state of research in a specific domain, effectively convey complex technical concepts, write a scientific paper, and deliver engaging presentations tailored for both academic and general audiences Typical tasks of the internship include  * Implementing cutting-edge robot perception and decision-making algorithms (e.g., reinforcement learning, learning-based control, semantic SLAM)  * Contributing to the benchmark software (e.g., safe-control-gym) and maintaining the repository  * Conducting real-world robot experiments (e.g., flying vehicles, mobile manipulators)  * Collaborating with graduate students and senior researchers to develop and verify theoretical findings  * Documenting findings in scientific writing and presenting them to internal and external research groups Salary: Compensation details, tailored to the candidate's qualifications, experience, and work location, will be shared during the interview.
Job Requirements:	* Interest in robotics research and interest in exploring and/or developing a profile for an academic career;  * Strong programming skills in Python and/or C++ and ability to quickly prototype algorithm design ideas;  * Experience in robotic software development (e.g., worked with ROS, implementation of perception, estimation, planning, control, or learning algorithms);  * Strong mathematical background and have taken relevant courses such as system control, machine learning, robot planning, and state estimation;  * Able to work independently on assigned tasks;  * Good communication skills and ability to work in a dynamic team environment;  * Completed the 3rd year of Engineering or related program before the start date of the internship;  * Any additional experience in scientific research is a plus.
Preferred Disciplines:	Computer Engineering Computer Science Electrical Engineering Engineering Science (Aerospace) Engineering Science (Electrical and Computer) Engineering Science (Machine Intelligence) Engineering Science (Physics) Engineering Science (Robotics) Math & Stats
All Co-op programs:	No
Targeted Co-op Programs:	Targeted Programs Professional Experience Year Co-op (12 - 16 months)

APPLICATION INFORMATION
Application Deadline:	Nov 15, 2023 11:59 PM
Application Receipt Procedure:	Employer Website
If by Website, go to:	http://tiny.cc/lsy-pey-application
Additional Application Information:	If you have any questions, please contact contact.lsy@xcit.tum.de and include “2024-2025 PEY” in the subject line.  Application Information:Note to PEY Co-op applicants: In addition to your application by email/website, please ensure that you select the “I intend to apply for this position” tab on the portal.  This will give us a record of your submitted application in the event that you will be invited for interviews.
U of T Job Coordinator:	Robin Kotisa

ORGANIZATION INFORMATION
Organization:	Technical University of Munich (TUM)
Division:	Main office
Website:	https://www.tum.de/en/

ADDITIONAL INFORMATION
Length of Workterm:	FIXED PEY Co-op: 12 months