Computer vision and machine learning for Ocean Worlds exploration

Job Details

Job ID: 10507

New ideas are all around us, but only a few will change the world. That’s our focus at JPL. We ask the biggest questions, then search the universe for answers—literally. We build upon ideas that have guided generations, then share our discoveries to inspire generations to come. Your mission—your opportunity—is to seek out the answers that bring us one step closer. If you’re driven to discover, create, and inspire something that lasts a lifetime and beyond, you’re ready for JPL.


Located in Pasadena, California, JPL has a campus-like environment situated on 177 acres in the foothills of the San Gabriel Mountains and offers a work environment unlike any other: we inspire passion, foster innovation, build collaboration, and reward excellence.


The Computer Vision Group at the Jet Propulsion Laboratory (JPL) in Pasadena, California, is looking for a postdoc to develop models the 3D geometry, appearance and chemical/biological composition of underwater hydrothermal vents. NASA and JPL are developing means of sampling, reconstructing and modeling seafloor hydrothermal vents, in order to prepare for future subsurface missions to Jupiter and Saturn's moons Europa and Enceladus. We are preparing to deploy a sensor package to study hydrothermal vents at the bottom of the Pacific Ocean, with instruments that reveal vent structure and chemical/biological composition. This position will support (1) the acquisition of data issued by the package, and its aggregation into a 3D spatial map, (2) the development of a cross-modal vent composition model that guides vent exploration and facilitates data visualization, and (3) data curation and publication. Drs. Renaud Detry and Laurie Barge (co-advisor) will serve as the postdoctoral advisors. The appointee will carry out research in collaboration with the JPL advisors, resulting in publications in the open literature. The position is available immediately, and will remain open until filled. 


Candidates must have a practical *and theoretical* understanding of classical ML (graphical models, dimensionality reduction, clustering, classification), familiarity with the basics of machine vision, and fluency in state-of-the-art deep learning models. The successful candidate will have a recent PhD in Engineering, Physics, Math, Computer Science or a related field, and fluency in C++ and in Python. This offer is not restricted to U.S. citizens.


Applicants should submit:

- a curriculum vitae (including publications)

- contact information for at least three referees

- date of availability

- (if available) a link to a code versioning account such as, illustrating past programming projects


Candidates who have received their PhD within the past five years since the date of their application are eligible. Postdoctoral Scholar positions are awarded for a minimum of one-year period and may be renewed up to a maximum duration of three years.

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