Robotics Vision Engineer

Robotic Vision Engineer for Automation of Ultrathin Brain Sectioning

 

The FlyWire Consortium, led by the Princeton Neuroscience Institute, recently released the first neuronal wiring diagram of an adult brain. The fruit fly connectome was obtained by processing electron microscopic brain images to reconstruct tens of millions of synapses between 100,000 neurons. With this historic milestone attained, neuroscience has clearly entered the connectomic era.

The image processing benefited from modern high performance computing and artificial intelligence. But the images were acquired from slices of the fly brain that were collected manually, in a manner that has remained essentially unchanged for over 50 years. We are building an engineering team to modernize the collection of ultrathin brain slices with a pick-and-place robot guided by computer vision. The task of the robot is to pick up slices floating on water and place them on substrates suitable for electron microscopic imaging. This is the kind of technological innovation necessary to scale up connectomics from flies to large mammalian brains more like our own.

 

We are seeking a robotic vision engineer to design and build the software system for computer vision, interface it with a robotic control system, and collaborate with a robotics engineer to control the pick and place operations.

 

This full-time position has an initial appointment of one year and possibility of renewal based on satisfactory performance. For more information, see these publications.

 

• Timothy J. Lee et al. Large-scale neuroanatomy using LASSO: loop-based automated serial sectioning operation. PLoS One 13:e0206172  (2018) .
  
• John Ngai. BRAIN 2.0: Transforming neuroscience. Cell 185, 4-8 (2022) .
  
• Sven Dorkenwald et al. Neuronal wiring diagram of an adult brain. bioRxiv 2023.
  

 

Key Responsibilities:

 

• Design and build software architecture for a vision-based guidance system of a robotic manipulator.
  
• Implement real-time high accuracy object detection and state estimation algorithms.
• Interface computer vision software system with robotic control system.
  
• Collaborate with robotics engineer to control pick-and-place operations.
  

Essential Qualifications:

 

• Masters degree in Electrical Engineering, Computer Science, or closely related field.
• Experience with convolutional nets and related computer vision algorithms.
• Proficiency in computer interfacing, software design and implementation.
• Strong problem-solving skills with a keen eye for technical details.
• Excellent collaboration and communication skills.

 

Preferred Qualifications:

 

• PhD degree in Electrical Engineering, Computer Science, or closely related field.
• Experience in robotics
• Experience with microscopy or other imaging.

 

 

Princeton University is an Equal Opportunity/Affirmative Action Employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law. KNOW YOUR RIGHTS

36.25

No

Yes

No

5/1/2024

No

No

Mid-Senior Level

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