Postdoctoral Associate- Large Scale Biophysical Modeling of Neurons

Summary

The goal of this project is to apply methods derived from large-scale optimization and optimal control towards the optimization of neuron models having a large number of electrical compartments. The developed techniques will be used to fit in vivo and in vitro electrophysiological data from murine CA1 pyramidal cells to understand the formation of their associated place fields. In addition, the same techniques will be applied to fit electrophysiological data from a visual neuron that detects impending collision in grasshoppers.

Job Duties

• Develop methods to efficiently optimize large-scale compartmental neuron models.
• Implement these methods through computer programing and test their efficiency using experimental data gathered in two model systems:
  • murine CA1 pyramidal cells
  • collision detection neurons in grasshoppers.

Minimum Qualifications

• MD or Ph.D. in Basic Science, Health Science, or a related field.
• No experience required.

Preferred Qualifications

• Familiar with systems of ordinary differential equations of Hodgkin-Huxley type used to model extended neurons.
• Experience in computer programing which will be central to the project's execution.
• Ph.D. in Computational Neuroscience, or a related field such as Electrical Engineering, Bioengineering, Computer Science, Biophysics or Applied Mathematics.

Baylor College of Medicine requires employees to be fully vaccinated -subject to approved exemptions-against vaccine-preventable diseases including, but not limited to, COVID-19 and influenza.

Baylor College of Medicine is an Equal Opportunity/Affirmative Action/Equal Access Employer.

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PD; CA; SN