Materials Knowledge Architect

Skills

About the Role

You will design scientific data models, schemas, and quality frameworks for materials data. You will lead partner-data ingestion, normalize and reconcile heterogeneous datasets, define schema mappings, resolve provenance issues, and translate research needs into ML-ready data assets.

Requirements

• Experience designing data models and schemas for complex scientific or technical domains
• Experience ingesting, integrating, and harmonizing data from multiple external sources
• PhD in Chemistry, Physics, Materials Science, Computational Chemistry, a related discipline, or equivalent scientific research experience
• Expertise in data representation, ontologies, data modelling, and data curation
• Knowledge of experimental, characterization, and computed materials data
• Knowledge of materials and chemical data sources including ICSD, Cambridge Structural Database, NOMAD, and Materials Project
• Python and SQL experience
• Experience with Pydantic, JSON Schema, pymatgen, ASE, Pandas, or Polars
• Experience with laboratory workflows and experimental data

Responsibilities

• Design data models for chemical, structural, and materials-property information
• Define mappings from external data sources to an interoperable internal representation
• Establish data quality, validation, deduplication, lineage, and provenance frameworks
• Lead ingestion and harmonization of partner data
• Assess new data sources and data-generation opportunities
• Define data formats and schema mappings with external providers
• Translate modelling needs into ingestion requirements and ML-ready datasets
• Improve data models, ingestion processes, and data quality

Benefits

• Equity
• 28 days holiday in DE, NL, and UK or 21 days holiday in JP, SG, and US, plus local public holidays
• 26 weeks paid parental leave for primary caregivers and 12 weeks for secondary caregivers
• Professional development budget