Computational Neuroscience Intern - Data Analysis and Modeling
25 – 60Emeryville, CAData ScienceHybridEntry level
Summary
Analyzes large-scale connectome and neurophysiology datasets, develops computational models of neural circuits, and implements data pipelines using Python/Matlab. Ideal for students in computational neuroscience or related fields with data analysis experience.
About the role
Responsibilities
- Process and analyze neurophysiology data such as electrophysiology, calcium imaging, or spike train recordings
- Analyze connectomics datasets, including neuronal connectivity graphs and anatomical reconstructions
- Develop computational models of neural circuits and network dynamics
- Implement data analysis pipelines and visualization tools
- Collaborate with researchers to interpret experimental data and generate hypotheses
- Contribute to documentation, reproducible workflows, and scientific reports
Qualifications and Experience
- Experience programming in Python and Matlab
- Familiarity with scientific computing libraries such as NumPy, SciPy, pandas, PyTorch, TensorFlow, or similar tools
- Basic understanding of neuroscience concepts, neural systems, or computational modeling
- Experience working with data analysis, statistics, or machine learning workflows
- Ability to work independently and communicate technical findings clearly
Preferred Qualifications
- Experience with connectomics or neurophysiology datasets
- Knowledge of computational neuroscience frameworks or simulators (e.g., NEST, Brian, NEURON)
- Experience with machine learning or dynamical systems modeling
- C++ programming experience is a strong bonus
- Familiarity with Linux, Git, and high-performance computing environments
Skills
PythonMatlabNumPySciPypandasPyTorchTensorFlowNESTBrianNEURONGitLinux