Ocean Data Specialist; Rtp V

Position: OCEAN DATA SPECIALIST (RTP V)
Location: St. John's

OCEAN DATA SPECIALIST  School of Ocean Technology/Centre for Applied Ocean Technology
Contractual Position to March 31, 2027 (with the possibility of extension)
A campus of Memorial University, the Fisheries and Marine Institute (MI) is North America's most comprehensive marine institute dedicated to education, training, applied research, industrial response, and technology transfer supporting ocean industries. Operating within MI’s School of Ocean Technology, the Centre for Applied Ocean Technology (CTec) provides research and development support, industry outreach, and scientific and technical advisory services to clients and partners, with expertise spanning ocean observation, ocean mapping, remotely operated vehicles (ROVs), aerial drones, autonomous surface vehicles (ASVs), and autonomous underwater vehicles (AUVs).

The Centre is based at The Launch, MI’s ocean innovation centre and a cornerstone facility in Canada’s ocean innovation ecosystem, located in Holyrood, Newfoundland and Labrador, approximately 35 minutes from St. John’s. This team works at the cutting edge of ocean technology, in collaboration with a wide range of marine sectors locally, nationally, and internationally, to enhance the safety, efficiency, sustainability, and profitability of maritime pursuits through the application of technology.
MI is a lead partner in Canada’s national ocean data network, the Canadian Integrated Ocean Observing System (CIOOS) and supports the contribution of ocean observation, mapping, and environmental datasets that facilitate open access to ocean information across Atlantic Canada. Through its applied research and technical expertise, MI helps advance ocean data management, interoperability, and knowledge sharing, enabling researchers, industry, governments, and coastal communities to make informed decisions about the marine environment.

This position will play a key role in the support of this network.
DUTIES  The Data Specialist is responsible for the development of sophisticated data products, including verification and quality assessment of real-time and archived data, and for supporting the development and application of artificial intelligence and machine learning models for ocean science and technology applications. These data products and models enable scientific, academic, and industrial users to understand, interpret, analyze and apply data acquired from a multitude of ocean sensors and platforms, including but not limited to autonomous vehicles, moored buoys, vessels, underwater video and imaging systems.

Duties may include preparing and managing large image, video and sensor datasets; developing data annotation and quality-control processes; designing, training, testing and optimizing computer vision and machine learning models for object detection, classification, tracking and image or video analysis; and evaluating model performance under varying environmental and operational conditions. The successful applicant may also integrate model outputs with fisheries, environmental, spatial and other marine datasets;

collaborate with subject matter experts to support model development and validation; and contribute to the deployment of data products and AI/ML models into operational research, monitoring, technology development or decision-support applications.
QUALIFICATIONS  Applicants must have a degree in Computer Science, Data Science, Artificial Intelligence, Electrical or Computer Engineering, or a related discipline, with a minimum of 3 years of relevant experience working with oceanographic, environmental, image, video or other scientific datasets and a strong quantitative and technical background. An equivalent combination of experience and training may be considered. Experience in artificial intelligence and machine learning, with particular emphasis on computer vision, deep learning, object detection, image classification, image segmentation, video analytics and model training and validation, is required.

Experience preparing and managing large datasets, data annotation, data augmentation, transfer learning, model optimization and performance evaluation would be considered…