NIWC - Undergraduate Student - Port Contamination Project (Task No. 71-342609)

Overview

The hourly rate for this position is $17.75 for Undergraduate II and$19.67 for Undergraduate III and is non-negotiable.

This position is open until filled

Under direction, incumbents must have course work in the discipline requested on the task order Statement of Work.

This Statement of Work covers the need for student services to assist with the development of a machine learning pipeline for evaluating water quality. Tasking could include (1) preparing satellite, buoy, and industrial/municipal spatiotemporal data for analysis, (2) performing exploratory data analysis, (3) creating data dictionaries, reports, and slides, and (4) assisting with the coding of deep learning models and other pipeline production requirements. This work will support water contaminant research at the Naval Information Warfare Center, Pacific (NIWC PAC).

NIWC PAC conducts research projects in a variety of domains in order to drive innovation and support warfighter information advantage. One area of interest is environmental risk to warfighter health and readiness. This machine learning pipeline is part of a larger effort that will help Navy commanders assess environmental risks and make informed operational decisions when service members might be exposed to environmental hazards. The student will primarily be involved in data science tasks such as preparing datasets, coding analyses, and writing reports. No human or animal testing is expected with this effort.

Responsibilities

The student contractor shall provide analytical and technical support in the following areas as specified under individual task orders, to the work sponsor.

Mathematics, Computer Science, Biology, Chemistry, or Physics:

• Preparing satellite, buoy, and industrial/municipal spatiotemporal data for analysis.
• Performing exploratory data analysis and generating data visualizations.
• Creating data dictionaries, reports of analyses, and slide decks of results.
• Assist with the coding and testing/debugging of a machine learning pipeline.
• Monthly Status Reports and Bi-Weekly Time Reports shall be in accordance with basic contract CDRL.
• Conducting relevant literature searches pertaining to the acceptance and execution of Model Based Systems Engineering (MBSE) practices.
• Submit Monthly Status Reports in accordance with the base contract.

Qualifications

Undergraduate Student 2: The student must be at the Junior or Senior level and have experience in 50% of the task requirements and be able to accomplish 50% of the work independently. Is not required to be an SDSU Student.

Undergraduate Student 3: Must have course work in the discipline requested on the task order Statement of Work. The student must be at the Senior level and have experience in 100% of the task requirements and be able to accomplish 90% of the work independently. Is not required to be an SDSU Student.

Minimum Qualifications Requirements:

Undergraduate Level 2-3 (Sophomore to Senior): Mathematics and/or Computer Science major preferred; relevant majors such as Biology, Chemistry, or Physics may be suitable given relevant coursework and/or work experience.

Required Coursework and/or relevant work and/or laboratory experience:

• Introduction to Chemistry, Biology, or equivalent
• Computer Science and Object-Oriented Programming or equivalent
• Probability and Statistics or equivalent

Desired Coursework and/or relevant work and/or laboratory experience:

• Introduction to Environmental Science, Oceanography, or equivalent
• Data Structures, Design and Analysis of Algorithms, or equivalent
• Computer Vision, Deep Learning, or equivalent

Additional Qualifications Desired:

• Python programming experience.
• Experience with CNNs or machine learning.
• Experience with GIS software.
• Independent/self-starter who can operate under minimal oversight.

ADDITIONAL APPLICANT INFORMATION:

• This position will require the employee to obtain and maintain a DoD Secret security clearance.
• The student will work in a hybrid format, with most work conducted virtually via Routine Telework. However, the student must be able to work at NIWC Pacific Bayside upon request.
• Due to the regulations established by the Department of Defense, only US Citizens may qualify.
• This is a student position and is limited to working 20 hours per week.
• This position will remain open until filled.
• Candidate must reside in California and live within a commutable distance from SDSU at time of hire.
• Job offer is contingent upon satisfactory clearance based on background check results (including a criminal record check).
• San Diego State University Research Foundation is an equal opportunity employer. Consistent with California law and federal civil rights laws, SDSU Research Foundation provides equal opportunity in employment without unlawful discrimination or preferential treatment based on race, sex, color, ethnicity, or national origin or any other categories protected by federal or state law.
• Employment decisions are based on an individual’s qualifications as they relate to the job under consideration. Our commitment to equal opportunity means ensuring that every employee has equal access to resources and support.
• SDSU Research Foundation complies with Titles VI and VII of the Civil Rights Act of 1964, Title IX of the Education Amendments of 1972, the Americans with Disabilities Act (ADA), Section 504 of the Rehabilitation Act, the California Equity in Higher Education Act, California’s Proposition 209 (Art. I, Section 31 of the California Constitution), and other applicable state and federal anti-discrimination laws including grant or contract terms and conditions related to funded program activities. Further the SDSU Research Foundation maintains a Nondiscrimination Policy that prohibits discriminatory preferential treatment, segregation based on race or any other protected status, and all forms of unlawful discrimination, harassment, and retaliation in all programs, policies, and practices.
• SDSU Research Foundation makes all employment decisions including, but not limited to, applicant screening, hiring, promotion, demotion, compensation, benefits, disciplinary actions, and terminations on the basis of merit.