PhD Intern (Geospatial Big Data)

Pacific Northwest National Laboratory

Seattle, WA, United States 🇺🇸

Job Description

The Hydrology Group at Pacific Northwest National Laboratory (PNNL) seeks a Geospatial Scientist with demonstrated experience in spatiotemporal analytics and remote sensing with an emphasis on big data handling of authoritative and non-authoritative data sources/streams, heterogeneous data fusion, machine learning and spatial optimization. The skills may be applied across multiple domains including rapid disaster response, critical infrastructure management, earth systems science and environmental modeling, alternative energy and food-energy-water nexus. This position will actively contribute research findings to the geospatial sciences that address current research challenges in the field.

Minimum Qualifications

Candidates must be currently enrolled/matriculated in a PhD program at an accredited college. Minimum GPA of 3.0 is required.

Preferred Qualifications

•Current Ph.D. candidate in Geography, Earth Sciences, Computer Science or related fields

•Publication experience

•Experience with a diverse set geospatial or potential geospatial data sources from authoritative (i.e., operational data) and non-authoritative (i.e., social media, volunteered geographic data) data sources.

•Demonstrated skill in programming, statistics, and machine learning

•Ability to operate on multiple compute platforms, i.e., Windows, Linux, HPC, Cloud

•Ability to obtain a federal security clearance in a timely manner

3.5 GPA or higher is preferred

Equal Employment Opportunity

PNNL is an Equal Opportunity/Affirmative Action Employer that is committed to hiring a diverse, talented workforce. EOE Disability/Vet/M/F/Sexual Orientation/Gender Identity. Staff at PNNL must be able to demonstrate the legal right to work in the United States.

Directorate: Energy & Environment

Job Category: Master’s and PhD Level Internships

Group: Hydrology

Opening Date: 2018-01-24

Closing Date: 2018-02-07


POSITION TYPE

ORGANIZATION TYPE

EXPERIENCE-LEVEL