Computational Science and Technology Advanced Research Studies (C-STARS) graduate researchers will collaborate with Oak Ridge National Laboratory (ORNL) scientists on solving problems of national and scientific interest, engage in educational and professional development opportunities, and present their research to ORNL's scientists. Participants will develop their skills to help solve scientific challenges using artificial intelligence, machine learning, and data science. They will learn from ORNL mentors who have expertise in computational research and/or domain sciences such as physics, materials, or biology. Research projects may include any research areas that support ORNL missions in the basic and applied sciences, energy, and environment, including but not limited to nuclear systems design and safety, theory and modeling of plasmas, climate change model predictions, transportation systems, sensors and controls, materials theory and simulation, quantum materials, and supercomputing.
The C-STARS program is administered by the STEM Workforce Development Unit of the Oak Ridge Institute for Science and Education (ORISE), which is managed by Oak Ridge Associated Universities (ORAU) for the U.S. Department of Energy.
All contingencies of an appointment offer must be met before the applicant can begin an appointment.
Participants who are foreign nationals must receive approval and clearance from the U.S. Department of Energy. This process is initiated by ORNL and could take more than ten weeks. Foreign nationals must also show proof that they have a valid immigration status, which allows them to receive a stipend. Once an offer has been made, the ORISE Immigration Office can assist with obtaining and filing immigration documents.
We also must have, for all participants:
Appointment Period and Renewals
Appointments are available in all current research and development programs at the laboratory. There are no citizenship requirements for the C-STARS program, although specific research projects may have additional restrictions. The program accepts applications at any time. Appointments are for a minimum of three months or for as long as twelve months, with possibility for extensions.
Participants receive a competitive biweekly stipend based on their educational level, research area, and experience. The stipend is taxable.
Applicants must be enrolled in a master’s or doctoral degree program at an accredited institution, or hold a recent (within the past 12 months) Master's degree, or have a Master's equivalency, in a science, technology, engineering or mathematics (STEM) area. Applications may be submitted at any time during the year, and appointments may begin at any time. Applicants also must be at least 18 years old before starting the program. The C-STARS program does not have citizenship requirements, but if the applicant is not a U.S. citizen, they must have a valid visa status allowing us to pay them a stipend.
Appointments involve a full-time commitment to the research program at ORNL, and the C-STARS participant must be in residence at ORNL during the entire period of the appointment. The participant's research must be conducted in a manner and according to a time schedule that meets the overall research needs of ORNL. To document the effectiveness of the program, participants are required to submit to ORISE a report when they renew or end their program tenure. These reports should summarize their research and include a copy of any publications resulting from their appointment. If future papers are published as a result of research they performed at ORNL, copies should be sent to ORISE.
C-STARS participants are required to have coverage under a health insurance plan and must provide proof of such coverage. It is your responsibility to secure insurance coverage before arriving at the appointment site.
Additional recommended qualifications:
• Experience with parallel and system programming
• Excellent communication skills (written and oral)
• Expertise with C/C++, Python and/or Java
• Experience with artificial intelligence and/or machine learning
• Experience with optimization, continuous learning, and reinforcement learning algorithms
I certify that I have completed coursework towards a degree in science, technology, engineering, mathematics, or a related field.