Applications are invited for a research software developer position in the lab of Dr. Stephanie Jones at Brown University. The level of the hire depends on experience. Our group combines human electrophysiological recordings and computational neural modeling techniques to study the mechanisms and meaning of brain dynamics in health and disease. We collaborate extensively with animal electrophysiologists and clinicians to develop data-constrained models that are translationally relevant. The software developer / research associate will work with a team of researchers at Brown, Mass General Hospital, and Yale to help develop a new software tool for circuit-level investigation of human magneto- and electro- encephalography (MEG/EEG) signals: Human Neocortical Neurosolver, HNN (https://hnn.brown.edu). The goal of this software is to provide the community with a user-friendly tool to develop and test hypotheses on the circuit origin of their data. The hired candidate will help support and expand HNN’s capabilities, including software development and working with researchers to apply HNN to specific neuroscience questions. Duties will also include development of tutorials, online resources, and participation in workshops aimed at training the community in the use and applicability of HNN.
Candidates should have a Bachelor’s, Master’s, or PhD in computer science, neuroscience, biomedical engineering, and/or related field. Strong Python programming skills are required, and experience with neural modeling, particularly NEURON, is preferred. Familiarity with MEG/EEG analysis methods and/or non-invasive brain stimulation is also beneficial. Candidates should be able to work in a dynamic, interdisciplinary, and fun work environment.
Interested candidates should send a cv and a brief description of qualifications and research interests to the Jones lab manager Dylan_S_Daniels@brown.edu.
Internal Number: 355355355
About Stephanie Jones Lab Brown University
The Jones lab at Brown University combines experimental and theoretical techniques to study human brain dynamics. Our mission is to develop biophysically principled models of neural circuits that bridge electrophysiological measures of brain function to the underlying cellular and network level dynamics. We aim to translate an understanding of the network mechanism underlying measured brain signals into strategies to improve disrupt function.