Lynker Technologies
Acoustician Level 2 Part Time - Cetacean Data Analysis & Processing Support

US-HI-Honolulu

Job ID: 2026-1572
Type: Part-Time
# of Openings: 1
NOAA - Honolulu HI

Overview

Lynker Corporation is seeking to hire one (1) part-time Acoustician Level 2 to support a contract with NOAA’s National Marine Fisheries Service (NMFS). This is a year-round, part-time position anticipated at approximately 940 hrs per year that may be performed on-site or remotely, with anticipated travel in support of meetings, workshops, and field activities. The position is anticipated to begin on September 30, 2026. Hiring for this position will be contingent on contract award. *Lynker will be operating under its FLOAT joint venture, a NOAA ProTech Fisheries 2.0 prime contract holder.

NOAA NMFS uses passive acoustic monitoring data to support cetacean population assessments and analysis of ocean soundscapes across the Pacific Islands Region. The tasks for this position will support larger analysis efforts at PIFSC. Work will include analysis of datasets collected from stationary, drifting, moored, towed, and autonomous platforms to evaluate cetacean vocalizations, behavior, occurrence, and relationships to habitat and environmental conditions.

Responsibilities

Essential Duties and Responsibilities

• Analyze passive acoustic monitoring datasets collected from stationary recorders, towed hydrophone arrays, drifting recorders, autonomous gliders, and other acoustic platforms.
• Develop, test, validate, and refine automated cetacean detection, classification, and localization approaches.
• Conduct quantitative analyses of cetacean occurrence, abundance, seasonality, habitat use, and acoustic behavior.
• Characterize cetacean call types and evaluate relationships between acoustic detections and environmental or anthropogenic factors.
• Perform statistical analyses supporting marine mammal stock assessments and ecological research.
• Analyze underwater soundscape datasets and compute ambient noise metrics across multiple temporal scales.
• Evaluate long-term acoustic trends and assess natural and anthropogenic sound sources within monitored ecosystems.
• Validate automated classifiers through manual review and annotation of acoustic datasets.
• Support acoustic analyses associated with autonomous Seaglider deployments and other emerging monitoring technologies.
• Contribute to acoustic propagation modeling and evaluation of species-specific detection performance.
• Maintain reproducible analytical workflows using MATLAB, Python, R, GitHub, and NOAA Fisheries data management standards.
• Document analytical methods, maintain analysis logs, and support preparation of reports, manuscripts, conference presentations, and technical summaries.
• Collaborate with NOAA scientists, project partners, and working groups to advance passive acoustic monitoring methodologies and research objectives.

Qualifications

The Acoustician selected should have the following minimum requirements:

• Master’s degree in marine biology, oceanography, acoustics, fisheries science, statistics, computer science, or related field
• At least two (2) years of relevant experience
• Working knowledge of underwater acoustic theory and practice, including acoustic propagation, sound measurement, and standard signal processing techniques
• Experience developing, testing, and validating automated detectors and classifiers for passive acoustic datasets
• Experience processing acoustic data to extract soundscape and ambient noise measurements at hourly to yearly timescales
• Ability to design, execute, and interpret statistical analyses of animal abundance to evaluate patterns in occurrence or associations with habitat or fishery variables
• Prior experience drafting reports and presenting project results at scientific meetings
• Proficiency in MATLAB and R programming languages, including MATLAB-based acoustic analysis software Triton
• Current MS Office skills
• Proficiency with passive acoustic metadata databases such as TETHYS and Makara
• Proficiency in open science practices, including use of GitHub or other resources for maintaining and archiving analysis code

The Ideal Acoustician will have the following preferred qualifications:

• Experience with acoustic localization techniques, including evaluation of automated algorithms within PAMGUARD and development of novel processing and evaluation code

About Lynker

Lynker is a growing, employee owned business, specializing in professional, scientific and technical services. Our continually expanding team combines scientific expertise with mature, results-driven processes and tools to achieve technically sound, cost effective solutions in hydrology/water sciences, geospatial analysis, information technology, resource management, conservation, and management and business process improvement.

We focus on putting the right people in the right place to be effective. And having the right people is critical for success. Our streamlined organization enables and empowers our talented professionals to tackle our customers' scientific and technical priorities – creatively and effectively.

Lynker offers a team-oriented work environment, and the opportunity to work in a culture of exceptionally skilled professionals who embrace sound science and creative solutions. Lynker's benefits include the following:

• Personalized career growth plans for every employee

Lynker is an E-Verify employer.

Lynker is an equal opportunity employer and makes all employment decisions based on merit, qualifications, and business needs. We do not discriminate on the basis of race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, marital status, veteran status, or any other legally protected status under federal, state, or local laws.

*This position is advertised through our joint venture, FISH and Lynker Ocean Alliance Team (FLOAT), a partnership between Lynker and Fisheries Immersed Sciences Hawaii (FISH) serving the NOAA ProTech Fisheries 2.0 IDIQ contracting vehicle.