The Van Hooser laboratory of Neural Circuits at Brandeis University in Waltham, MA USA ( has received funding for a 2-year NIH BRAIN grant to develop an open-source software interface for accessing neuroscience data. The interface is not a file format, but rather is a consistent platform-independent and language-independent standard that allows neural data analysis code to be written in a manner that is independent of the file format and the manner in which the experimental or model data are organized on disk. 

The software development goals of this project are a) to finish development of the framework, b) to develop a small initial set of common data analysis “apps” that conform to the interface, c) to modify commonly used open-source analysis tools such as KlustaKwik, KiloSort, Ca_source_separation to conform to the interface, and d) to develop a graphical user interface for navigation of data and analysis results. Several data sets at Brandeis and at labs participating in the BRAIN program will be curated and metadata added so that they conform to the interface to facilitate adoption and analysis by third parties, including theorists, other experimental labs, or amateur scientists. The interface will be thoroughly revised in response to data curation efforts and according to results of 7 user evaluation and tutorial events, including sessions at third party user experience labs.

The priority is to develop a powerful but easy-to-use interface that is accessible to neuroscientists with different levels of computing experience, including “data-knowledgable” users (who do not code), “data-expert” users (very experienced coders), and the much larger group of “data-literate” users (who have light coding experience but who are not computer scientists). 

We are seeking an experienced SOFTWARE DEVELOPER/DATA SCIENTIST with neuroscience research experience and an interest in open-source software development to perform much of the development and curation, to develop tutorial material, and to maintain open-source software repositories. The candidate could be a postdoctoral fellow or a staff member, depending upon the candidate’s career goals.

The job responsibilities include the following:

Software development: The primary job responsibility will be a main role in developing an open source data interface for neuroscience data that is easy to learn and use.

Revision and collaboration: The development project is organized so that the interface and code will be revised several times. The candidate will need to welcome the idea of being part of a highly collaborative process with feedback and code editing by other users.

Development of tutorial material: The candidate will prepare tutorial material for new users to access on the web and material for in-person tutorials. The tutorial material will also be subject to evaluation and revision.

Repository management: The candidate will manage the GitHub spaces, responding to bug reports, requests for features, pull requests, etc.

Publications: The candidate will participate in the preparation of research publications in neuroscience and/or data science journals describing the results, corrections, and conclusions from our user interface tests and software development.

Travel and presentation at conferences, tutorials: The candidate will play a major role in tutorial events at SFN 2019 (Chicago) and SFN 2020 (Washington), and will be expected to attend and present at 1 additional conference annually. 

Skills required:

Academic skills: The candidate should be an expert software developer. An understanding of basic neuroscience analysis techniques is essential. Good teaching skills and good English writing are a must.

Programming languages: The candidate will develop software using Matlab, Python, Git, and GitHub. The candidate should have sufficient experience with object oriented approaches and version control software.

Interpersonal skills: The candidate will develop and modify open-source material. The candidate should have experience interacting with a wide community of users and programmers in an inclusive and respectful manner.

The project will be directed and overseen by Stephen Van Hooser (PI) and Olga Papaemmanouil (Co-I). Van Hooser is a neuroscientist with experience with 2-photon calcium imaging in vivo, extracellular and intracellular recording in vivo, and neural modeling. Papaemmanouil is a computer scientist with expertise in data management systems and interactive big data analytics and exploration.

Interested applicants should send a CV and the names and contact information of 3 references to