Require Clinical Ontologist at Symbolic AI

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Building one of the World's most advance Artificial General Intelligence (AGI) technology with amalgamation of Connectionist AI (Artificial Neural Network), Symbolic AI, Predictive Memories and Knowledge Based AI. is the first healthcare application using this technology. More on soon as we unravel the unsolved healthcare problems.

Post : Clinical Ontologist

No of Posts : 05

Job Description

  • Standardization of clinical data from various data sources and ontologies: SNOMED, LOINC, RxNorm, UMLS etc.
  • Ontology building by mappings and linking relationship between medical concepts.
  • UMLS curation and dictionary filtration.
  • Educate and support the software development team by solving their queries regarding disease, procedure, and other medical terminology and taxonomy.
  • Provide quality assurance of automated mapping using Health Language terminology application of data to standardized medical terminologies.
  • Editing/updating medical taxonomy/ontology for hierarchical and semantic relationship.
  • Training Artificial General Intelligence Software tools for learning on Medical Knowledge Graphs
  • Manage medical records interoperability by mapping clinical content to national terminology standards like RxNorm, SNOMED and UMLS
  • Coordinate with internal and external organizations to enhance the quality of mapping and interoperability
  • Build databases for clinical content analysis
  • Deploy standard terminology within the organization
  • Contribute to the design of clinical data dictionaries for storing and retrieving clinical reference information
  • Terminology and Ontology Research and Product Development
  • Research and development of advanced terminology search engines and user interfaces for clinical terminology management.
  • Curating and integrating terminology content (including SNOMED CT, LOINC, RxNorm and various flavors of ICD-9 and ICD-10 and some other terminologies) in the Healthcare Data Dictionary.
  • Working closely with natural language processing experts and engineers to develop information extraction methods in an agile work environment.
  • Providing technical expertise in national and international terminology standards including: SNOMED, ICD-9, ICD-10, and other UMLS source vocabularies.

Candidate Profile
• Comprehensive knowledge of drugs (pharmacology) and diseases.
• Working knowledge of medical taxonomy/ontology.
• Working knowledge of UMLS, LOINC and/or SNOMED CT.
• Ability to evaluate medical literature relevant to a specific clinical problem.
• Training abilities for bioinformatics projects.
• Computer operational skills.
• Knowledge of different versions on windows operating system and/or Linux.
• Proficient in searching medical contents and references on internet.

Additional Information
Experience : 0-1 year
Qualification : B.Pharm, M.Pharm, Pharm.D
Location : Hyderabad
Industry Type : Pharma/ Healthcare/ Clinical research
Functional Area : Medical Ontology
End Date : 20th July, 2019

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Posted by
Rakesh Chandra

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