Evidence Synthesis Information Scientist
Job in
Blacksburg, Montgomery County, Virginia, 24062, USA
Listing for:
Digital Library Federation
Full Time
position
Listed on 2025-12-17
Job specializations:
-
Research/Development
Research Scientist, Data Scientist
Salary/Wage Range or Industry Benchmark: 65000 USD Yearly
USD
65000.00
YEAR
Job Description & How to Apply Below
Minimum Compensation in Local Currency: $65,000 minimum dependent on qualifications and experience
Maximum Compensation in Local Currency: $65,000 minimum dependent on qualifications and experience
Hourly or Salary? Salary
Description
Job Description: The Evidence Synthesis Information Scientist, reporting to the Assistant Director, Evidence Synthesis Services, will join the collaborative Evidence Synthesis Services team in supporting evidence synthesis research at Virginia Tech for Blacksburg, Roanoke, the National Capital Region, and other university locations and affiliates. The successful candidate will be an ambassador for high-quality evidence synthesis at Virginia Tech; as an expert in search techniques and synthesis methods such as systematic reviews;
provide guidelines-based consultation, outreach, live and asynchronous training, and additional support for systematic reviews and other topics related to evidence synthesis; explore emerging tools, resources, and methods for evidence synthesis; supervise student assistants; serve as subject area liaison to one or more departments, institutes, or program areas; and contribute to supporting the Virginia Tech community in adoption of open and collaborative research practices.
Participate in serving on institutional or professional committees, and demonstrating a commitment to team efforts, service excellence, and Virginia Tech’s Principles of Community.
Required Qualifications:Masters degree from an ALA-accredited graduate program; OR an advanced degree in a position-related field, such as: data science, epidemiology, health sciences, life sciences, social sciences, public health, statistics, agricultural science, environmental science, engineering, or other related fieldsDemonstrated experience leading systematic review search strategy development, implementation, and documentationDemonstrated experience conducting systematic review searches in databases such as MEDLINE/Pub Med, CAB Abstracts, Scopus; other databases via platforms such as EBSCOhost, Pro Quest, Web of ScienceDemonstrated experience using and supporting others in evidence synthesis search methodologies, guidelines, and standards such as those recommended by Cochrane, Campbell, the Collaboration for Environmental Evidence; PRISMA, MECCIR, ROSES; etc.Demonstrated experience providing reference or research assistance and instruction/training in an academic, research, or clinical environmentDemonstrated experience in outreach, relationship building, and collaboration with a variety of groups such as faculty, students, or vendorsDemonstrated experience designing, planning, implementing, and maintaining complex projectsDemonstrated experience collaborating with colleagues to problem-solve and share knowledge, with a commitment to team efforts and service excellenceDemonstrated ability to effectively understand and communicate complex ideas to novice and scientific/technical audiencesExcellent writing and communication skills, including experience with proofreading publication manuscripts and following a variety of style guidesPreferred Qualifications:Demonstrated experience peer reviewing systematic review search strategiesDemonstrated experience using and/or training others in evidence synthesis project management tools, such as:
Covidence, Distiller
SR, Rayyan, or othersDemonstrated experience providing support or instruction for developing and refining research scope; critical appraisal of primary research; systematic data extraction or coding; approaches to synthesizing qualitative evidence; and/or archiving supplemental materialDemonstrated experience with conducting and/or interpreting primary researchDemonstrated experience managing and/or analyzing dataDemonstrated experience in using and/or training others in text or data mining, machine learning, language models, or other AI tools for evidence synthesisDemonstrated experience supervising students and/or staff#J-18808-Ljbffr
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