Symbrosia Inc
Biosystems Sensor Integration Fellow
About the Organization
Symbrosia is a Hawaiʻi-based aquaculture company pioneering innovations in seaweed cultivation to drive a more sustainable and resilient future. Our work sits at the intersection of marine biology, agriculture, and product innovation, transforming how ocean resources are cultivated and applied across industries.
Our flagship product, SeaGraze®, is a red seaweed-based feed additive that reduces methane emissions from livestock while improving production efficiency. Building on our expertise in marine bioactives, we are also developing Lumara, a premium skincare line powered by polysaccharides extracted from sustainably farmed seaweed.
At Symbrosia, we are vertically integrating cultivation, processing, and product development to unlock the full potential of ocean-grown materials. Our team is focused on building scalable, science-driven solutions that deliver both environmental impact and commercial value.
Fellowship Description:
Sensor Deployment & Integration
Support remote configuration and deployment planning of biomass sensors
Develop installation protocols and scaling playbooks
Troubleshoot system issues alongside engineering
Data Integration & Operational Use
Translate biomass data into actionable insights for cultivation teams
Support development of dashboards or reporting tools
Ensure data usability for non-technical operators
System Optimization
Identify improvements in sensor performance and reliability
Analyze growth trends to inform cultivation strategy
Collaborate on iteration of sensor design and deployment methods
Field Coordination & Continuous Improvement
Work cross-functionally with on-site teams to validate real-world performance
Support maintenance protocols and system monitoring
Contribute to SOPs for sensor-enabled cultivation systems
Working Style & Structure
Remote with structured communication loops with farm + engineering teams
Weekly syncs + async reporting
Strong emphasis on clear, actionable outputs
Qualifications:
Background in Engineering, Data Science, Environmental Engineering, or related field
Interest in sensor systems, aquaculture, or applied biological data
Experience with hardware systems, data pipelines, or analytics preferred
Ability to translate technical outputs into operational decisions
Organized, proactive, and systems-oriented
Time Commitment: 30 hours / week