Summary

The Hennig Lab is seeking a postdoctoral researcher passionate about understanding how neurons in the brain support multiple behaviors, using tools from computational theory and modeling. In our lab you will perform cutting-edge research at the intersection of neuroscience, machine learning, and neural data analysis. Potential research projects are flexible based on the candidate's interest, and include topics such as multi-task learning, meta-learning, and reinforcement learning.

Job Duties

• Plans, directs and conducts research related to theory, modeling, and analysis of behavioral and neural data.
• Evaluates and analyzes neural and behavioral data.
• Develops novel behavioral experiments, and runs them on online participants and/or patients at Baylor/St. Luke's Supports collection of electrophysiological recordings from human patients at Baylor/St. Luke's.
• Summarizes research findings and publish results in research journals.
• Mentors junior lab members on related projects.
• Provides intellectual contribution to other ongoing projects in the lab, and assists PI in shaping the long-term research strategies and directions.
• Demonstrates commitment to fostering a collaborative lab environment and promoting positive group dynamics. 
   

Minimum Qualifications

• Ph.D. in Chemistry, Computational Sciences, Computational Biology, Structural Biology, Computer Science, Bioinformatics, Statistics, or related disciplines. May also include Ph.D. in Biology or Biomedical Sciences in combination with an M.S. or extensive multidisciplinary experience in one of the above quantitative fields.

Preferred Qualifications

• Candidates within their final year of a Ph.D. are especially encouraged to apply.
• Ideal candidates will have prior research experience in neuroscience, solid programming skills, and comfort with linear algebra and statistics.
• Experience in analyzing extracellular neural recordings is ideal but not required.
• Experience with PyTorch or Tensorflow is ideal but not required.