Doctoral Student In Robotics And Generative Artificial Intelligence

Company Description Clemson University is a public land-grant research institution that has served the people of South Carolina for more than 130 years. With an R1 classification, Clemson is recognized as one of the nation’s most active research universities, offering robust opportunities for cutting-edge inquiry and innovation. The University is committed to developing international leaders and upholding core values of honesty, integrity, and respect across all academic programs. With more than 160,000 graduates and a strong focus on diverse fields and impactful applications, Clemson provides a collaborative environment for students to grow as scholars and professionals. Doctoral students join a community of determined individuals working to create meaningful impact in the professions that inspire them.

Role Description The Doctoral Student in Robotics and Generative Artificial Intelligence will conduct original research at the intersection of robotics, machine learning, and generative AI, contributing to publications in top-tier conferences and journals. Day-to-day activities include designing and implementing algorithms, building and testing robotic systems, running simulations and experiments, and analyzing quantitative and qualitative data. The role involves close collaboration with faculty advisors and research teams, participation in research group meetings, and presentation of findings in seminars and academic conferences. This is a full-time, on-site role located in Clemson, SC, requiring regular presence in university labs and research facilities.

Qualifications

• Candidates should possess strong technical skills in robotics, including robotic control, motion planning, and hands-on experience with robotic platforms or simulators.
• Candidates should possess solid foundations in artificial intelligence and machine learning, such as deep learning, reinforcement learning, and generative models (e.g., GANs, diffusion models, large language models).
• Candidates should possess programming and software development skills, ideally in languages such as Python, C++, or MATLAB, along with experience using relevant libraries and frameworks (e.g., PyTorch, TensorFlow, ROS).
• Candidates should possess research and analytical skills, including experimental design, data analysis, scientific writing, and familiarity with publishing in peer-reviewed venues.
• Candidates should possess strong communication and collaboration abilities, with capacity to work effectively in diverse, multidisciplinary teams and present complex ideas clearly to technical and non-technical audiences.
• Relevant qualifications include a completed or near-completed master’s or bachelor’s degree in robotics, computer science, electrical or mechanical engineering, or a closely related field, and a demonstrated interest in pursuing a PhD.
• Beneficial qualifications include prior research experience in robotics or AI, contributions to open-source projects, experience with high-performance computing or cloud-based experimentation, and a commitment