Full Job Description
National Energy Technology Laboratory (NETL)
How to Apply
A complete application consists of:
A current resume/CV, including academic history, employment history, relevant experiences, and publication list
Two educational or professional references
Please send a CV to Kelly Rose at email@example.com
All documents must be in English or include an official English translation.
If you have questions, send an email to NETLinfo@orau.org. Please include the reference code for this opportunity in your email.
9/1/2020 11:59:00 PM Eastern Time Zone
Through the Oak Ridge Institute for Science and Education (ORISE), the Geo-Analysis & Monitoring Team within NETL's Research & Innovation Center's Geological & Environmental Systems directorate is looking for a motivated student interested in performing research focusing on geological and environmental sciences to evaluate environmental impacts and risk assessments associated with domestic energy resource development. The student will learn about and take part in a research project involving the combination of conventional geologic methods with data science and machine learning. The applicant should have coursework and a solid background in geology and be prepared to learn more about integration of data science methods into geoscience, and collaborate with experts on the Team in support of project goals that focus on improving data search and characterization using machine learning algorithms for subsurface, geologic systems associated with onshore and offshore sedimentary basins aligned with oil, natural gas, and carbon storage systems.
As a NETL intern, you will support the Geo-Analysis & Monitoring Team to identify, format and characterize key datasets using a combination of conventional and data science driven methods. These datasets are the foundation to conducting advanced research that integrates and quantitatively evaluates key attributes of shale gas, ultra-deep water and frontier regions to estimate potential risks related to oil/natural gas development, rare earth elements characterization, and/or carbon storage. Another goal of this research project is development and adaptation of data science and machine learning methods that focus on improving data search and characterization.
The Team is looking for applicants with a background in geology and subsurface systems. Applicants should have expertise and coursework demonstrating bachelor’s or more advanced knowledge of sedimentary, geologic systems. Knowledge of oil, gas and subsurface carbon storage/sequestration science is also helpful but not required. Applicants should also demonstrate good communication and collaboration skills, and willingness to learn as they will be collaborating with a multi-disciplinary team of data scientists. Applicants with experience and expertise interpreting subsurface data (e.g. well logs, seismic, cross section, isopach and structure maps) are also desirable. Experience or willingness to learn coding languages such as Python, and data science tools such as Jupyter notebooks, etc. are also desired.
Degree: Any degree .
Communications and Graphics Design (2 )
Computer Sciences (17 )
Earth and Geosciences (23 )
Engineering (27 )
Environmental and Marine Sciences (13 )
Life Health and Medical Sciences (47 )
Mathematics and Statistics (11 )
Nanotechnology (1 )
Other Physical Sciences (12 )
Physics (16 )
Social and Behavioral Sciences (32 )
I certify at the time of application that:
I will have received an undergraduate degree no more than two years before the date of the internship appointment.
I am currently pursuing a master's degree.
I have not received a master's degree but currently pursuing a doctoral degree.