Machine Learning Data Research Scientist ( R-00067493 )
Looking for an opportunity to make an impact?
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The Leidos Research Support Team supporting the National Energy Technology Laboratory (NETL) is seeking a Machine Learning Data Research Scientist to join our Team in Albany, OR as part of our Workforce Development Program. This opportunity will allow side by side execution of research with world-class scientists and engineers using state of the art equipment to contribute to new areas of basic and applied research.
The employee will leverage their data science capabilities to participate in studies relating to offshore research that focus on developing tools and managing data that provide critical insights into understanding subsurface hazards, risk assessment, and informing infrastructure integrity. This work will involve a multidisciplinary team participation alongside other data scientists, engineers, geologists and computer scientists to support the priorities of the DOE Fossil Energy and Carbon Management mission space.
TERM OF COMMITMENT: This research position is intended to be a term position, with varying levels of commitment that are not expected to last longer than 2 years. You will be informed prior to applying what length of commitment is anticipated. Also, those who successfully fill a term position, may be invited to apply for an additional term. Nothing in this paragraph is intended to create an employment contract. Employment will remain at will.
If this sounds like the kind of environment where you can thrive, keep reading!
Primary Responsibilities Include:
- Applying artificial intelligence/machine learning methods to analyze geological and geophysical data.
- Building and modifying software tools using Python, creating stand-alone scripts, writing new applications.
- Collaborating with geologists and other science researchers to assist in accomplishing project-related tasks.
- Building relationships with internal and external clients.
- Creating and delivering oral and poster presentations of results.
- Master’s degree or currently enrolled in a master’s program leading to a degree in data science, computer science, math, geography, geo-statistics, geospatial science, environmental science, petroleum engineering or similar field with less than 2 years of prior relevant experience.
- Robust coding experience including Python and familiarity with tensor flow.
- Demonstrable skills in the application of various machine learning methods.
- Willingness and interest in learning geological information related to data (i.e. offshore subsurface topics and spatial data).
- Familiarity with software development, UI/data libraries, source code repositories, and ArcGIS
- Familiarity with geologic systems and geohazards