General Summary:

The Byrnes lab at UMass Boston () is seeking a postdoc to aid in completion of a NASA Funded project, "Using Hyperspectral Imagery to Assess the Effects of Warming on New England Kelp Forests". The postdoc would begin at their earliest convenience as part of the team (Crystal Schaaf, Nima Pahlevan, Rodrigo Garcia, Marc Borrelli, Tom Bell, Bob Chen, Arthur Elmes). The postdoc will be to work with the project team to complete analysis and write up of data collected over two years of field campaigns consisting of data from Hyperspectral Drones, PRISMA and EnMap satellites, in situ drop camera data, in situ spectral data, side scan sonar, and diver collected data. The postdoc will also have opportunities to teach workshops, if they desire, and to collaborate with a deep learning team at the University of Zargoza. The position presents the opportunity for multiple novel and potentially high impact publications. The position is for one year with the team supportive of applying for future funding.

Examples of Duties:

• Apply tuned machine learning models to hyperspectral drone data around the Gulf of Maine.

• Work on calibrating PRISMA and EnMap imagery against validated hyperspectral drone data.
• Process in situ reflectance data gathered over the last two years for collaboration with colleagues on an inversion modeling paper.
• Collaborate with colleagues at the University of Zargoza developing deep learning approaches to drop camera imagery to identify kelp from survey data.
• Build and apply machine learning models with the above data to model kelp bed locations throughout the Gulf of Maine.
• Apply causal statistical models to use environmental data layers and kelp predictions to derive inferences about biological processes driving kelp beds in the Gulf of Maine.
• Mentor graduate students working with Landsat and drop camera imagery to understand change in benthic algae over time.
• Give presentations at national and international conferences.
• Present at a departmental research seminar.
• Interface with the relevant NASA DAAC to archive project data and code.

Qualifications:

A PhD by time of starting position in either Ecology, Remote Sensing, Marine Biology, Environmental sciences, or other related disciplines before starting the position is required. Strong quantitative, statistical, and programming skills are necessary. Previous experience with remote sensing and hyperspectral data is required. Experience with machine learning is a plus. Knowledge of kelp forest ecology or shallow water remote sensing in any system is not required but will help the postdoc achieve more rapid success.

Part of the project involves other members of the project team using SCUBA for validation in summer 2024. If the postdoc wishes to incorporate that into their work, they are required to have AAUS or equivalent certification.

Additionally, the incumbent must be:

• Proficient with R, Python, or other programming language.
• Have the ability to follow oral and written instructions.
• Have a strong attention to detail.
• Have a strong background in record keeping and experience with or interest in data management; Github experience strongly preferred.
• Strong oral and written communication skills.
• Experience or desire to work as part of a multi-disciplinary team.

Application Instructions:

Please apply online with your resume, cover letter and list of three references.

Review of candidates will begin following the application closing date.

Salary Range: Commensurate with experience

This is a non-union exempt position.

UMass Boston is committed to the full inclusion of all qualified individuals. As part of this commitment, we will ensure that persons with disabilities are provided reasonable accommodations for the hiring process. If reasonable accommodation is needed, please contact or 617-287-5150.