The Scientific Curation Team at SciBite-Elsevier is fundamental to our Software Solutions. The team manages high quality ontologies and produces curated vocabularies which feed into our technology stack. We also work with teams across Elsevier to deliver training, content and innovative solutions to our customers to support their Scientific discoveries. As a SciBite-Elsevier curator, you will be integral in creating content, and helping solve key challenges for our Life-Science customers.
Key Responsibilities:
· Working to deliver exceptional customer support. The successful candidate will work with teams across Elsevier and partner companies to deliver bespoke customer solutions.
· Updating and continual improvement of SciBite’s key scientific content.
· Organizing the ontology pipeline to deliver ontologies into the heart of SciBite tools, for the Life Sciences and beyond.
· Demonstrating and training customers on use of SciBite tools.
· Writing blogs, reports and papers, and giving presentations at public meetings and workshops.
· Developing SOPs, and devising and implementing key curation workflow improvements
Qualifications/Skills/Experience:
· PhD or MSc in a Life Sciences subject
· Strong interpersonal skills, and confident in representing Elsevier at customer and public meetings
· Experience of building and working with biomedical ontologies
· Experience curating biological/clinical data within a pharma/drug discovery/life sciences environment
· Familiarity with major bio and chemo-informatics public databases and ontologies
· Bring the right ‘Can Do’ approach to fit our company culture
· Experience of working independently and under pressure
· Ability to identify problems and apply creative solutions
· Excellent written, verbal and presentation skills
Additionally, any experience in the following would be advantageous:
· Experience in customer-facing or Professional Services roles
· A scripting language such as Python, accessing RESTful APIs, use of regular expression
· Using Git/GitHub
· Exposure to text-analytics and text-mining and an understanding of how these can aid drug discovery and development
· Interest in Machine Learning / AI
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