Machine Learning Image Recognition Analyst Needed
Integrated Statistics is looking for a Machine Learning Image
Recognition Analyst to support the National Oceanic and Atmospheric
Administration (NOAA) National Marine Fisheries Service (NMFS) Northeast
Fisheries Science Center (NEFSC). The NEFSC Protected Species Branch
(PSB) mission includes evaluating threats to species and populations due
to anthropogenic activities. The Machine Learning Image Recognition
Analyst will be working on protected species bycatch, which is when
protected animals get caught or entangled in fishing gear. Bycatch can
negatively affect species such as dolphins, sea turtles, protected fish,
and whales by harming animals, contributing to population declines, and
impeding population recovery.
project, video data that was collected on commercial fishing vessels as
part of a fisheries monitoring program is being reviewed so that bycatch
events and species can be identified and further analyzed. Since such
interactions are relatively rare events, these data are sparse and an
automated review of the video can be a realistic and cost effective way
to identify actual or probable protected species interactions.
Machine Learning Image Recognition Analyst will develop analyses of
image data to inform bycatch estimates and assessments of fisheries
impacts on protected species. The Analyst’s ultimate goal is to develop
an algorithm automating the detection and identification of protected
species visualized on video from gillnet, bottom trawl, and other types
of fishing gear. The Machine Learning Image Recognition Analyst will
begin by curating and developing a protected species (bird, mammal,
turtle) image library utilizing video and still image data sets. After
that, the Analyst will explore approaches to automating image analysis,
developing algorithms in support of machine learning applications and
annotated training data sets.
Qualifications and Skills
familiarity with the data and processes, including image review, data
analysis, image data set curation, preparing and processing data.
Identifying, acquiring and/or generating, and characterizing data and
- Investigating and determining suitable machine learning technologies
and available open-source resources (software applications, coding, and
curated datasets) for a data-sparse context.
- Training and testing models.
- Developing machine learning based video analysis; creating a system and workflow for conducting the automated image analysis.
- Generating reports that use the image data to inform assessments of fisheries impacts on protected species.
- BS in Computer Science, Data Science, Mathematics, or a closely related field.
proficiency in at least one programming language relevant to machine
learning and artificial intelligence for image recognition (VIAME,
TensorFlow, Python, R, Matlab, C++, etc.)
- Demonstrated skill and
knowledge in applying artificial intelligence and machine learning
techniques to image data for image recognition.
- Experience in photogrammetry and information extraction using machine learning, deep neural nets for image recognition.
- Project development and management skills are desirable. Statistical programming skills are desirable.
- Coursework and/or exposure to biological data is desired, but not required. The skills needed are in programming, not biology.
- US citizenship and presence. Ability to comply with EO 14042.
- Excellent written and oral communication skills.
record of success in working remotely. Demonstrated ability to
contribute timely deliverables and work collaboratively as part of a
The position is expected to be full-time for one
year, the rate of pay depends on skills and experience, and the position
is eligible for the benefits described on the Integrated Statistics
website. The position will probably start remotely but with the goal of
intermittent in-person work at the NEFSC lab in Woods Hole, MA.
Statistics is an equal opportunity employer and will not discriminate
against any employee or applicant on the basis of age, color,
disability, gender, national origin, race, religion, gender identity,
sexual orientation, veteran status, or any classification protected by
federal, state, or local law. Consistent with its obligations under
federal law, Integrated Statistics is committed to taking affirmative
action to employ and advance in employment qualified women, minorities,
disabled individuals, special disabled veterans, veterans of the Vietnam
era, and other eligible veterans. For assistance with accessibility of
applications, posters, forms, and/or documents, please email the
Integrated Statistics office.