Engineering and Science Liaison
Functional Area: Libraries
School Area: Libraries, MIT Press, Tech Review
Employment Type: Full-Time
Employment Category: Exempt
Visa Sponsorship Available: No
Working at MIT offers opportunities, an environment, a culture – and benefits – that just aren’t found together anywhere else. If you’re curious, motivated, want to be part of a unique community, and help shape the future – then take a look at this opportunity.
ENGINEERING AND SCIENCE LIAISON, MIT Libraries, to support research and teaching in engineering and science disciplines in assigned areas. Responsibilities include locating or developing datasets/software/other information sources; assisting with literature reviews; assisting researchers with managing and documenting their research outputs; teaching in the library program on information citizenship where students and researchers critically evaluate current information ecosystem practice and develop ways to promote openness and equity; evaluating tools, platforms, and infrastructure that support research; designing and leading projects to gather and analyze data about emerging research and teaching practices; and developing systematic, ongoing learning initiatives around emerging topics in data-intensive and computational research.
REQUIRED: MLS/MLIS or a degree in engineering; at least three years’ relevant experience including working with data and scholarly information in engineering research; ability to carry out a liaison program of support through outreach, building relationships, and a systematic approach for providing services; ability to consult with and advise researchers in science, engineering and computing fields; familiarity with trends in science and engineering, e.g., interdisciplinary and global collaborations, translating research into practice, open science, open access, and open data; teaching experience, which may include designing online modules, working with project teams/research groups, co-designing student assignments, articulating learning outcomes and assessment, or planning workshops/class sessions; strong collaboration, organizational, and communication skills; experience working with data sets, statistical analysis software, R, python, and other data analysis tools/programs; familiarity with tools and platforms for collaborative research, including GitHub, electronic lab notebooks, open source and open science tools, and data repositories; experience gathering data using APIs; and familiarity with the application of machine learning to research problems. Applications must include cover letter and resume. Priority will be given to applications received by November 8, 2019. Job #18090-8
MIT is an equal employment opportunity employer. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, sex, sexual orientation, gender identity, religion, disability, age, genetic information, veteran status, ancestry, or national or ethnic origin.