The Post Doctoral Associate performs scientific research and studies under the supervision of managing staff. Moreover, the Post Doctoral Associate promotes institutional recognition through literal contributions to the scientific community.
Conducts research on specific areas of study as assigned.
Prepares research reports and technical papers for publishing.
Investigates the feasibility of applying a wide variety of scientific principles and theories.
Maintains substantial knowledge of state-of-the-art principles and theories.
Develops advanced analytical models and systems and provides solutions and analyses to support strategic and tactical decisions.
Adheres to University and unit-level policies and procedures and safeguards University assets.
Support the PI in launching new interdisciplinary robotics research and educational initiatives in the ECE Department and across the College of Engineering, including foundational program design and curriculum integration.
Lead and contribute to research involving AI-powered and AI-enabled robotic systems, including deep reinforcement learning, computer vision, and human-robot interaction.
Facilitate strategic collaborations across departments within the College of Engineering and with the UM Miller School of Medicine, particularly in the area of medical robotics for surgical and assistive applications.
Assist with setting up the PI’s new research lab, including hardware/software integration, experimental platforms, and safety protocols.
Support preparation and submission of competitive grant proposals to federal funding agencies (e.g., NSF, NIH).
Mentor and help recruit and train graduate students and undergraduate researchers in robotics, mechatronics, and machine learning.
Design and conduct experimental studies involving robotic platforms such as dual-arm manipulators, mobile robots, and wearable/exoskeleton robotic systems.
Present research at national and international conferences and co-author peer-reviewed publications in leading robotics and AI venues.
Doctorate degree Medicine (MD) required
No previous experience required
Learning Agility: Ability to learn new procedures, technologies, and protocols, and adapt to changing priorities and work demands.
Teamwork: Ability to work collaboratively with others and contribute to a team environment.
Technical Proficiency: Skilled in using office software, technology, and relevant computer applications.
Communication: Strong and clear written and verbal communication skills for interacting with colleagues and stakeholders.
Ph.D. in Electrical and Computer Engineering, Robotics, Mechanical Engineering, or a closely related Engineering field.
Extensive experience in robotics system design, real-time control, and embedded systems integration.
Demonstrated expertise in artificial intelligence, including reinforcement learning, computer vision, and deep neural networks applied to robotics.
Track record of peer-reviewed publications and active participation in interdisciplinary research projects.
Strong programming skills (Python, C++, MATLAB) and experience with software tools such as TensorFlow, ROS, Gazebo, and OpenCV.
Familiarity with robotic hardware platforms (e.g., Kinova robotic arms, UAVs, mobile robots) and real-time operating systems.
Excellent communication skills and ability to work in cross-functional and interdisciplinary teams.
Demonstrated initiative, creativity, and problem-solving ability in research and development environments.
Experience with grant writing, mentoring students, and collaborative academic or industry research is preferred.