tiffsail
Journals are the medium through which scientific discoveries are shared - from cancer research to aerospace engineering. science.ai allows new, innovative journals to go to market faster and works with the world's largest publishers to redefine their digital journal infrastructure.
We are looking for a full stack or front end JavaScript engineer with proven experience who understands the importance of maintainable code and comprehensive tests and who values simple, composable services. We have a pragmatic approach to architectural and technology choices, and hope you will too.
Our core infrastructure relies on react, react-router, redux / reselect and PouchDB on the frontend and Node.js, CouchDB and a sprinkling of ZeroMQ on the backend.
You'll be a critical member of our team, and your code will have significant impact on the science.ai platform. If you think you might be a good fit, please send an email along with evidence of your work (GitHub profile...) to [email protected].
Standard Analytics (Techstars NYC 2014) is hiring a Machine Learning / Data Engineer to help us organize the world’s scientific knowledge (full post: http://www.standardanalytics.io/jobs#dataengineer). One of our primary goals is to make knowledge discovery more accessible, contextual, and anticipatory, all driven with the power of machine learning, AI, and the semantic web. As a data engineer at Standard Analytics, you will have the unique opportunity to not only take full advantage of the copious amounts of open-access data and text available, but also the large number of scientific articles published through our platform.
Some of the challenging problems we are currently trying to solve include: Multi-label large-scale text classification, scientific entity recognition, data linking across multiple ontologies and resolution within multiple knowledge bases, deep contextual information retrieval, and Q&A.
We are looking for someone to join us full time in NYC as a core member of our machine learning / data science team. If you think you might be a good fit, please send an email along with evidence of your work (GitHub profile, etc.) to [email protected].