Job Description
<h3>π Description</h3> β’ Translate otologic domain knowledge into structured, computable forms such as ontologies and knowledge graphs.
β’ Design and prototype NLP and Information Extraction (IE) components to extract relevant otologic concepts, relations, and insights from unstructured clinical data.
β’ Develop algorithms and models to explore different Symbolic AI approaches.
β’ Contribute to the design of online and federated learning pipelines for continuous model refinement.
β’ Administer data sets, including responsibilities related to data quality, data maintenance and archiving, analysis, documentation, and reporting.
β’ Collaborate closely with medical experts to align clinical meaning with technical models.
β’ Partner with software engineers to ensure smooth handoff of models and data structures for implementation.
β’ Monitor state-of-the-art AI technologies and provide assessments of their suitability to the companyβs software applications. <h3>π― Requirements</h3> β’ PhD or Masterβs degree in Computer Science, Biomedical Informatics or a related technical field.
β’ Solid knowledge of biomedical ontologies, taxonomies and controlled vocabularies.
β’ Solid knowledge of AI & ML technologies outside of LLMs.
β’ Experience working in healthcare/medicine is a big plus.
β’ Ability to extract structured insight from unstructured records.
β’ Experience in Designing Knowledge Graph and Description Logic Inference systems.
β’ Experience in creating custom training datasets, including data collection, preprocessing, and augmentation.
β’ Ability to synthesize complex medical concepts into usable AI components.
β’ Skilled in Python and modern ML frameworks
β’ Excellent communication and time management skills. <h3>ποΈ Benefits</h3> β’ Competitive salary based on experience and qualifications.
β’ Flexible, Remote environment.
β’ Health, vision, and dental benefits included.