Address
Form of work
SalaryOverview:
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 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 robotics engineer to design and build the robot, interface it with a control system, and collaborate with a robot vision 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). https://doi.org/10.1371/journal.pone.0206172
Preferred Qualifications:
This position is subject to the University's background check policy.
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 RIGHTSStandard Weekly Hours: 36.25 Eligible for Overtime: No Benefits Eligible: Yes Probationary Period: 180 days Essential Services Personnel (see policy for detail): No Physical Capacity Exam Required: No Valid Driver’s License Required: No Experience Level: Mid-Senior Level : #LI-JJ1
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 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 robotics engineer to design and build the robot, interface it with a control system, and collaborate with a robot vision 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). https://doi.org/10.1371/journal.pone.0206172
John Ngai. BRAIN 2.0: Transforming neuroscience. Cell 185, 4-8 (2022). https://doi.org/10.1016/j.cell.2021.11.037
Sven Dorkenwald et al. Neuronal wiring diagram of an adult brain. bioRxiv 2023. https://doi.org/10.1101/2023.06.27.546656
Responsibilities: - Build a robotic manipulator with sub-millimeter accuracy.
- Design a real-time closed-loop control system for the manipulator.
- Collaborate with robotics engineer to control pick-and-place operations.
Essential Qualifications:
- Masters degree in Mechanical Engineering, Electrical Engineering, or closely related field.
- Proficiency in mechanical design, CAD software, computer interfacing, and electronics.
- Knowledgeable in robot kinematics, inverse kinematics, dynamics and control system
- Demonstrated ability to troubleshoot mechanical and electronic systems.
- Strong problem-solving skills with a keen eye for technical details.
- Excellent collaboration and communication skills.
Preferred Qualifications:
- PhD degree in Mechanical Engineering, Electrical Engineering, or closely related field.
- Experience with micromanipulators.
This position is subject to the University's background check policy.
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
