MISSION TO METRICS

The mission of The Ocean Cleanup is to develop advanced technology to rid the world’s oceans of plastic. To do so, we need to assess our technology’s ability to catch plastics in the ocean and to meet our cleanup targets. The steering strategy is crucial to optimize our catch with the shift from passive to active systems.
“Since the garbage patch is highly heterogeneous, actively steering to the hotspots will significantly increase our efficiency” – Yannick Pham, Steering Strategy Manager

PROFESSIONAL QUALIFICATIONS

• Fluent in English
• Master’s or bachelor’s degree in natural sciences or engineering with strong computational skills
• Strong experience in Python, MATLAB, or any other data science programming language (Julia, R…)
• Experience in data science is highly valued
• Knowledge of high-performance computing techniques is a plus

PERSONAL QUALIFICATIONS

• Intrinsic motivation to work on our ambitious and meaningful mission
• Able to perform well in a fast-paced and highly challenging environment
• Meticulous, detail-oriented, structured
• Team player, diplomatic
• An affinity with numbers
• Excellent communication skills
• Ability to work with tight deadlines

• Improve The Ocean Cleanup’s plastic dispersal model and understanding of plastic accumulation, combining model outputs and measured data:
• Familiarize yourself with the existing Lagrangian plastic dispersal model framework.
• Familiarize yourself with the data environment, mainly:
• Drifting GPS buoys track, and the analytics tools that go with
• Camera-based plastic detection
• Weather/Circulation data
• Validate sea-surface current analysis techniques to exhibit local convergence candidates (using Lyapunov exponents and Lagrangian coherent structures) against measured data
• Use System 002/03 to measure density data (extraction and camera data).
• Develop a method to parametrize and calibrate meso and submeso-scale eddy diffusivity
• Get involved in other data science projects:
• Run statistical analysis on the world’s largest beach cleanup database to better understand the beaching phenomenon
• Continue the development of a beaching model using data science techniques (Bayesian relief networks, Machine Learning)