What part will you play?
• Ability to manipulate and analyze large scale, high-dimensionality data from varying sources
• Experience in creating and maintaining knowledge graph data structures for SPECT & PET Scanners
• Experience in semantic consistency checking
• Ability and experience in data integration
• Experience in manipulating unstructured, semi-structured and fully structured datasets
• Capability to understand and model a domain in interactions with the partners
• Readiness to work in uncertainty regarding the resolution of a problem, the existence of means to resolve it and, sometimes, in the absence of precise objectives
• Autonomous and responsible; organized and structured in initiatives and work
• Detail-oriented and able to keep a global vision of the issues and their solutions
• Graph Analytics NLP, Machine Learning & Deep learning
• An open mind; desire to learn the most appropriate language/technology to solve a given problem Use your skills to move the world forward
• You have Masters/PhD in Computer Science or a related discipline from a reputed institute with grass-root experience of 3+ years in architecting data analytics and machine learning applications using knowledge graphs
• Experience in semantic web related specifications and tools
• Knowledge of knowledge graph consistency and coherency checking
• RDF, RDFS (preferably also OWL) • Querying & data manipulation in SPARQL
• Programming skills (e.g. Python, Java, basic HTML…)
• Experience with ETL processes and tools (cleaning, conversion, …)
• Understanding of inference in RDF, RDFS and OWL (including profiles)
• Knowledge of property graph formalism (e.g. Neo4j, Gremlin, Tinkerpop, …)
• Awareness of authoring ontologies using tool like Protégé (need not be an expert but should at least have that ability)
• Decent awareness of RDF stores like Blazegraph and/or GraphDB to go with corresponding SPARQL knowledge that is mentioned.
