MBARI’s Summer Internship Program provides an opportunity for talented college students (undergraduate and graduate) and educators to work directly with MBARI scientists, engineers, and communicators.

MBARI’s state-of-the-art facilities and equipment, including research vessels, remotely operated vehicles (ROVs), and autonomous underwater vehicles (AUVs), offer educators and students unique opportunities to collaborate on advanced research and development projects. The program immerses interns in collaborative teams as they learn innovative research and engineering techniques and improve communication skills. Each intern will have an MBARI mentor who will supervise a specific project for a 10-week duration. Interns also serve as peer-mentors to each other. There is a stipend (2025 stipend was $22/hour) and the program is full-time. MBARI will try and assist with housing for those interns coming from out of the area. Please see How to Apply for more specific information about the application process.  

Please DO NOT contact staff/mentors to ask about the internship program. MBARI will host one or more general zoom sessions (dates to be determined) where questions can be asked about the program and/or the application process. 

The MBARI Summer Internship Program is generously supported through a gift from the Dean and Helen Witter Family Fund and the Rentschler Family Fund in memory of former MBARI board member Frank Roberts (1920-2019) and by the David and Lucile Packard Foundation. Additional funding is provided by the Maxwell/Hanrahan Foundation.

Program Dates

June 08 – August 14, 2026

Applications are now being accepted – the application period will close at 0800 AM (Pacific timezone) on March 9, 2026. 

How to Apply

Learn about the project opportunities and application requirements.

How to Apply

Internship Papers

Internship papers from the most recent five years.

ALL PAPERS

Project Opportunities

 
Antarctic polynyas productivity from BGC-Argo floats perspective: Coastal polynyas are open water area surround by sea ice. They are hotspots of high biological productivity and physical processes, driving deep water formation, overturning circulation, and could be highly impacted by the recent changes in sea-ice patterns (Hoobs et al., 2024; Doddridge et al., 2025). Due to the remote nature of these places, studying them remain extremely challenging. While satellites are powerful and allow us to depict events happening at the surface, they cannot provide insights on water columns processes. This can be partly resolved using Biogeochemical (BGC) Argo floats deployed by the Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM). They provide a 3D picture and have unraveled critical changes in the most remote area of the ocean. The main objective will be to look at phytoplankton productivity in a chosen Southern Ocean polynya system, explore its relationship with seasonal drivers (light, sea-ice, nutrients) and the fate of carbon exported to the deep ocean.
This project is heavily coding oriented, so candidates should be comfortable with programming (MATLAB preferred). As part of the Carbon group, candidates will have the opportunity to learn about biogeochemical sensing capabilities on Argo floats, how to access and analyze BGC Argo data. Knowledge in oceanography is desirable, but not mandatory.
  1. Doddridge, E. W., Hobbs, W., Auger, M., Boyd, P. W., Chua, S. M., Cook, S., Corney, S., Emmerson, L., Fraser, A. D., Heil, P., Kelly, N., Lannuzel, D., Li, X., Liniger, G., Massom, R. A., Meyer, A., Reid, P., Southwell, C., Spence, P., Steketee, A., Swadling, K. M., Teder, N., Wienecke, B., Wongpan, P. & Yamazaki, K. (2025). Impacts of Antarctic Summer Sea-Ice Extremes. PNAS Nexus, Volume 4, Issue 7, pgaf164. https://doi.org/10.1093/pnasnexus/pgaf164
  2. Hobbs, W., Spence, P., Meyer, A., Schroeter, S., Fraser, A, D., Reid, P., Tian, R, T., Wang, Z., Liniger, G., Doddridge, E., & Boyd, P, W. (2024). Observational evidence for a regime shift in summer Antarctic sea ice. Journal of Climate, 37(7), 2263-2275 https://doi.org/10.1175/JCLI-D-23-0479.1

Duane Edgington

Automated classification of deep-sea and surface imagery: MBARI has a rich collection of underwater video, photographs, and micrographs, much of which has been professionally analyzed and curated, as well as ocean surface images collected by a drone. We are exploring state-of-the-art automated classification and analysis techniques. This intern will join us in this exploration, testing selected techniques against collections of videos or images to detect and classify organisms of interest to MBARI scientists. One area we are exploring is self-supervised and weakly supervised methods. A background in computer science is required; coursework or experience in machine learning and computer vision would be an ideal background.

Gene Massion

Autonomous Coastal Profiling Float: We have a broad spectrum of potential projects spanning a range of disciplines suitable for a summer intern. An overview of the project can be found at https://www.mbari.org/coastal-profiling-float/.  We are looking for an intern with some experience and a strong interest in one or more of the following topics and a particular interest in developing technology for oceanographic research applications.

1) Design and development of embedded microcontroller based systems.  The ST Microelectronics STM32 family is of particular interest.
2) Design and development of embedded C/C++ software.  Training and/or experience in rigorous software testing methodologies is of particular interest.
3) Automated test systems and web based applications using LabView.
4) Mechanical design of robotic oceanographic research equipment using Solidworks CAD tools

 
Autonomous Water Sampler Development (FIDO): FIDO (Filtering Instrument for DNA Observation) is an autonomous water sampling system designed to collect and preserve Environmental DNA samples. The system is being developed as an ecosystem monitoring tool to support long-term autonomous observation of aquatic system. For an internship project, you will choose what interests you from a related set of topics. Potential subjects include: (1) Mechanical design improvements for reliability and performance (sample handling mechanisms, actuator systems, fluid manifolds); (2) Extended characterization, calibration, validation of FIDO’s sensing systems under a range of environmental conditions; (3) Design for manufacturability and assembly optimization. We are looking for an intern with interests in mechatronics, instrumentation, environmental testing, or aquatic sampling technology. Experience with CAD tools, micropython, or data analysis tools (R/Python/MATLAB)  would be valuable.

Steve Haddock

Biodiversity and Bioluminescence: Steve Haddock’s lab aims to characterize and monitor the diversity and behavior of gelatinous plankton (jellyfish and their kin) in the deep sea and open ocean. For an internship project, you will choose what interests you from a related set of topics. Potential subjects include: (1) Bioluminescence biochemistry and genetics; (2) Population genetics of a zooplankton group (e.g. ctenophores, pelagic snails, siphonophores); (3) Generating interactive taxonomic keys (e.g., using Xper3); (4) Deep-sea ecology from the video annotation archives (stats and R); (5) Comparative bioinformatics and transcriptome analyses. For an overview of some unanswered questions, see our review papers (bit.ly/arms-deep and bit.ly/arms-biolum)

Video Lab

Deep-sea video data miningMBARI has recorded almost 30,000 hours of stunning high-resolution video from thousands of deep-sea research missions. The Video Lab annotates and manages this video archive of biological, chemical, geological, and physical aspects of the Monterey Canyon and beyond. Together with MBARI software engineers, we have developed the Video Annotation and Reference System (VARS)—including most recently a suite of VARS Machine Learning (VARS-ML) tools and workflows—to facilitate cataloging and querying of this valuable database. We are seeking an intern with interest and experience in ecological and/or data science studies to utilize our VARS resources for designing and executing a project (e.g., research project, data products/tools, new analysis/study designs) with a focus on identifying and analyzing data trends, evaluating data quality, and devising methods for enhancing the usability and accessibility of these valuable deep-sea ecological data.

Raúl Nava and Cassandra Burrier

Developing a communications campaign for the 30th anniversary of MBARI’s Summer Internship Program: As MBARI’s Summer Internship Program marks its 30th anniversary, the Science Communication (SciComm) Team seeks an intern to develop and launch an outreach campaign about the program’s legacy. Responsibilities will include interviewing past participants, MBARI staff, and current interns, and creating visual and written content for MBARI’s website and social media channels. This project is ideal for an intern with experience in science communication and storytelling, and requires strong writing and video production skills. Experience in video editing, photography, or journalism is strongly desired. In addition to the required application materials, please include samples of writing and multimedia content. Former interns are eligible to apply for this position.

Jim Barry and Olivia Soares Pereira

Ecology of invertebrate communities on organic-fallsOrganic falls (wood and whale falls) provide food for specialized invertebrate communities, creating island-like habitats considered hotspots of biodiversity in the deep sea. Wood blocks and bones were deployed at three depths in the Monterey Canyon to study the colonizing invertebrate communities and whether environmental variables play a role in defining them. We are looking for a summer intern to help sort these samples in the laboratory and analyze the data. The intern will be doing a lot of microscope work, and basic knowledge on invertebrate major groups are preferred but not required. The intern will also have the opportunity to be involved in other of our lab activities, including research on deep-sea corals and seamounts and potentially going to sea with the research team on one-day deep-sea research cruises.

Biological Oceanography Group

Environmental DNAUnderstanding temporal changes and spatial shifts in species assemblages is key to assessing ocean health and informing management actions. Traditional biodiversity surveys, however, are costly in both time and resources and often lack sufficient coverage in space and time. One of the focuses of our lab is the use of environmental DNA (eDNA) as a tool to track changes in biodiversity. eDNA can detect the presence of a wide variety of organisms, from microbes to whales, with just a liter of seawater and has the potential to be automated. As part of our projects at MBARI, eDNA samples have been collected along the California coastline from diverse environments including kelp forests, seamounts, deep sea, and coastal waters. The intern will have the opportunity to gain experience in laboratory-based molecular techniques and/or, data and bioinformatic analysis from these collections.  In the laboratory the intern can explore biodiversity shifts using long-read nanopore sequencing methods. Opportunities will be provided to participate in sample collection at sea and to assist in developing or optimizing new eDNA assays/primers.

Andrew Hamilton and Scott Jensen

Lithium Battery Performance Testing for Energy Harvesting Applications: Energy harvesting and storage comprise a core engineering challenge related to advancing a long term presence of un-crewed instrumentation and vehicles in the ocean.  As MBARI is working to advance these capabilities through the use of wave-energy harvesting systems and autonomous underwater vehicle docking, the required battery systems meet some unusual technical challenges.  In particular the charge/discharge cycle profile encountered is unique to these systems and therefore relatively poorly understood.  This internship will work to characterize the lifespan of lithium cells in these challenging conditions by setting up tests and performing life-cycle testing at a range of charge/discharge profile types.  In addition to collecting and analyzing this data, the intern will have the opportunity to explore balancing techniques that may be applicable to extending the cell life, as well as understanding all aspects of our wave-energy harvesting and vehicle docking technology.

 
Modular Aerial Imaging System: The MBARI UAV Program is developing a modular aerial camera and sensor system that can be deployed across a range of Uncrewed Areial Systems (UAS) to expand our ocean surface sensing capabilities. For an internship project, you will choose what interests you from a related set of topics. Potential subjects include: (1) Mechanical design and prototyping of camera mounting and stabilization systems; (2) Development of remote sensor control systems; (3) Software development for image capture, georeferencing, or data management. We are looking for an intern with interests in mechanical design, embedded systems, or marine observation technology. Experience with CAD tools, microcontrollers, and Python would be valuable.
Pushyami Kaveti and Giancarlo Troni
 
Multimodal Perception for Underwater Robots: Robotic platforms such as AUVs and ROVs have revolutionized ocean exploration with their ability to sense and map challenging underwater environments. Robust perception is a key capability that allows robots to interpret complex, dynamic scenes and operate autonomously under uncertainty. This internship will focus on developing novel sensing and mapping techniques that fuse multimodal data, including optical imagery, sonar, and navigation sensors, to build rich, high-resolution 3D reconstructions of benthic environments. The candidate will explore modern learning-based rendering methods, such as Gaussian splatting and neural radiance fields (NeRFs), and adapt them for underwater environments characterized by low light, turbidity, and dynamic visibility conditions. Interns will gain hands-on experience in perception algorithms, sensor fusion, and data-driven modeling while contributing to an active research effort at the intersection of robotics and computer vision. Candidates should have proficiency in Python programming and familiarity with deep learning libraries such as PyTorch or TensorFlow. Coursework or experience in computer vision and machine learning is required. Knowledge of CUDA-based deep learning libraries is a plus.

Giancarlo Troni and Sebastian Rodriguez

Scalable Marine Robotics: Ocean exploration has been widely developed thanks to marine robotics, whose platforms are currently being used on several applications, such as accurately mapping the seafloor in high-resolution and continuously tracking animals in midwater. However, these platforms are not scalable, many are still too expensive to build and operate, and access to scientists, and therefore ocean exploration and discovery, is limited due to underwater vehicle navigation among others. Potential intern projects will use current MBARI’s robotics platforms to enable scalable marine robotics navigation in complex terrain. Efforts include sensor calibration and alignment of sensor data and visual-inertial navigation based on simultaneous localization and mapping (SLAM) framework. The work will combine elements of estimation, computer vision, software development and data analysis. Candidates should have basic competence in C/C++ and Python programming. Experience with robotics will be advantageous.

 
Théo Picard and Monique Messié
 
Tracking the surface origin of deep sinking particles in the California Current: Station M is a long-term abyssal time series station located off the California coast that includes carbon fluxes measured at a depth of 3400m. This carbon originates from sinking organic particles produced by surface phytoplankton and zooplankton. However, due to local dynamics affecting sinking particle pathways, identifying the location of their surface origin remains challenging. In this project, the intern will explore a recent machine learning method for reconstructing the origin of sinking particles captured at Station M by training a neural network based on a set of numerical simulation experiments and applying it to real satellite observations. The analysis will help better connect the planktonic production observed at the surface with the deep fluxes measured at Station M. Applicants with experience using Python and machine learning are preferred.
 
Video Annotation and Reference System Machine Learning Vector Database Project: MBARI’s VARS-ML (https://tinyurl.com/ynrz6t9e) team is quickly becoming a world leader in the application of machine learning techniques to analyze ocean imagery. At present, we have compiled a machine learning model training dataset of over 1.2 million labeled objects. We have run our models on imagery from a variety of ocean habitats, including surface waters down to depths of 5,000 meters. In 2026, we will develop a new vector database, storing image embeddings for these localized training data. Utilizing these image embeddings and the VARS-ML vector database, our internship project is to investigate novel uses for this rich dataset which may include datamining, outlier detection, similarity clustering, natural language search, zero-shot or few-shot classification, and cross-modal correlation (looking at correlation with other metadata, e.g., geolocation, depth, physical measurements). We seek an intern with machine learning and Python programming experience who is inventive and curious and will help us create new ways to understand our unique visual data.