Position
Europe
(Biology) Ontology Knowledge Engineer
MindWalk is a global biologics discovery company integrating Bio-native AI, deep data, and advanced lab research to accelerate discovery and development of therapeutic, anti-drug and diagnostic antibodies, peptide-based therapies, vaccines and beyond. We deliver end-to-end solutions spanning target exploration, discovery, engineering, characterization, production, and humanization—available as full-service partnerships, existing asset co-development or modular SaaS access. We partner with leading biotech and pharmaceutical organizations, applying our unified biointelligence ecosystem to advance next-generation biologics that improve lives.
Job Description:
We're looking for an ontology and knowledge engineer who can formally model the biology MindWalk works with: sequences, structures, assays, evidence, and the scientific claims built on top of them.
This is where knowledge representation meets biomedical depth. You'll decide what counts as the same entity across experiments, how evidence of different strength and status gets represented, and how existing biomedical standards can be reused or extended for MindWalk's needs.
Key responsibilities:
- Expand and maintain the canonical semantic model for MindWalk's biological, experimental, and scientific-claim objects.
- Define identity, versioning, and mapping rules for sequences, biological patterns, structures, assays, and derived data.
- Model evidence with its real epistemic status — supporting, contradicting, inconclusive, or missing — without flattening it into a single confidence score.
- Reuse and map biomedical standards (OBO Foundry, Sequence Ontology, ECO, OBI, PROV-O) where they fit, and extend them where MindWalk's biology has no exact match.
- Ship your models as production artifacts: RDF/OWL modules, SHACL shapes, and validation tests.
- Partner with data and platform engineers so your ontology plugs into the broader information architecture, not around it.
Requirements:
- Hands-on experience building production ontologies or biomedical knowledge graphs, not just academic modeling.
- Practical fluency in RDF/RDFS, OWL 2, SHACL, and SPARQL, with a clear sense of where ontology inference ends and application logic begins.
- Hands-on experience in traditional Information Management domains such as Master Data Management, Metadata Management, Data Governance and Data Security.
- Real experience in biomedical, pharmaceutical, or bioinformatics domains, with an ear for where the science gets messy.
- Comfort with identity resolution, provenance, and representing scientific uncertainty.
- An MSc or PhD in knowledge representation, bioinformatics, biomedical informatics, or a related field, or equivalent experience.
- Good written and oral communication skills in English.
- You are agile in planning and organizing your work. You are an excellent team player.
Strong candidates may also have:
- Broader data and information architecture experience: catalogs, lineage, data contracts.
- LinkML, ROBOT, SSSOM, or the Ontology Development Kit.
- Experience with LLM or agent workflows that consume ontology-backed context.
- AWS or other cloud-native deployment experience.