Summary

The group of Fabrizio Gabbiani at Baylor College of Medicine (BCM, Department of Neuroscience) is looking to hire a research technician to work on the optimization of biophysical models for single neurons. The project will be carried out in close collaboration with the group of Jeffrey Magee at BCM (also in the Department of Neuroscience) and that of Matthias Heinkenschloss at Rice University (in the Department of Computational Applied Mathematics & Operations Research). The goal of the 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. They are looking for a highly motivated scholar with the ability to bridge theoretical and experimental work in neuroscience. The technician be familiar with systems of ordinary differential equations of Hodgkin-Huxley type used to model neurons. In addition, the applicant will have experience in computer programing which will be central to the project’s execution. The position is best suited for a committed and inspired person, for example a recent college graduate that is looking for experience before applying for graduate school in Computational Neuroscience.

For more information: https://glab.research.bcm.edu/wp/

Job Duties

• Implements parameter optimization problems in Python and/or C++.
• Explores the performance of various algorithms.
• Simulates biophysical models using the NEURON package.
• Translates large-scale NEURON biophysical models in Python.

Minimum Qualifications

• Bachelor's degree in a Basic Science or related field. Four years of related experience may substitute for degree requirement.
• No experience required.

Preferred Qualifications

• B.S. degree in Neuroscience with a concentration in computational neuroscience or computer science .
• B.S. in a related field such as Electrical Engineering, Computer Science, Biophysics or Applied Mathematics.
• Experience in computer programing which will be central to the project’s execution is a plus.
• Recent college graduate that is looking for experience before applying for graduate school in Computational Neuroscience.
• Hands-on experience with biophysical modeling of neuron using Hodgkin-Huxley type models.
• Programming experience in Python and/or Matlab.
• Programming experience in C++.
• Familiarity with parameter optimization techniques.