The Marine Physical Laboratory Division (MPL) Division at SIO is seeking a Marine Mammal Research Associate to join an oceanographic research group studying marine mammals. Under supervision, the incumbent shall assist in analyzing marine mammal acoustic and anthropogenic sound data both manually and using automated detection and classification algorithms. Enter passive acoustic metadata into database and ensure information integrity. Assist in the development of analysis software including applications of unsupervised learning algorithms to acoustic datasets. Edit, maintain and run programs in Matlab and Python programming languages. Assist with creation and archiving of derived datasets and associated metadata.

Assist with coordination of day to day progress on research projects and deliverables. Assist with the preparation, mobilization, de-mobilization and ship-based set-up of oceanographic equipment. Identify and describe all marine mammal species encountered on cruises. Transcribe, analyze and plot data from marine mammal sightings. Assist in utilizing and servicing oceanographic equipment at sea. Assist in preparation of technical reports and verbal presentations. Assist with preparation of scientific publications and proposals. Interact with staff and graduate students.

This is a 50-100% variable career position with full medical and retirement benefits. Must be flexible and available to work variable hours 50%-100% of the time based on department needs; hours are set forth by the supervisor.

Must be able to travel. Remote-site and/or at-sea operations for field testing and experiments up to a maximum of 30 days per trip/year.

Overtime and weekends may be required.


B.S. in Biology, Physics, Engineering or Computational Science; or an equivalent combination of education and experience.

Demonstrated education and/or experience in marine mammal science.

Proven experience with marine mammal vocalizations and anthropogenic sounds including the ability to differentiate signals by species or source visually and aurally.

Demonstrated experience with acoustic data in studying marine mammals, anthropogenic sound and ambient noise.

Familiarity with PC's, email, Internet, general office tools and software.

Proficient skill using and modifying code for acoustic data processing using MATLAB, Java, Python, XML/XQuery.

Proven ability to organize acoustic data into clear, concise and descriptive content for scientific analysis.

Demonstrated experience with version control systems including Git.

Proven experience with supervised and unsupervised learning algorithms.

Strong ability to communicate professionally and effectively with academic, staff and student personnel, both verbally and in writing. Excellent English proficiency.


Job offer is contingent upon a satisfactory clearance based on background check results.

Must possess and maintain a valid California driver's license.