Computational Neuroscience Intern - Data Analysis and Modeling

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 Requirements 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 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 Hard Skills Python Matlab NumPy SciPy pandas PyTorch TensorFlow C++ data analysis machine learning Soft Skills independent work communication #J-18808-Ljbffr