At Genestack we are tackling the underlying computational and scientific challenges of bioinformatics in order to provide researchers with software tools that will streamline the discovery process and drive forward precision medicine, drug development, and bioinformatics research.
We’re looking for a Scientific Data Curator to help us build the structured, high-quality biomedical datasets. You’ll work at the intersection of biomedical knowledge, ontology management, and human-in-the-loop AI workflows — transforming unstructured content into machine-readable intelligence.
If you have a sharp eye for scientific detail, a passion for structured data, and experience navigating biomedical vocabularies, this role offers a unique opportunity to influence how AI systems interact with life sciences data.
In this role, you will:
- Read, extract, and normalise data from scientific documents, including research papers, experimental protocols, supplementary tables, and structured repositories.
- Curate and maintain controlled vocabularies and biomedical ontologies, including term mapping, version control, and governance of new term requests.
- Design annotation guidelines, review model outputs, and ensure human-in-the-loop feedback improves model performance.
- Maintain traceability and quality of curated data through auditable records, structured schemas, and defined acceptance criteria.
- Identify and correct errors in metadata and provide regular feedback on data quality metrics (e.g. coverage, consistency, accuracy).
- Work with cross-functional teams — including bioinformaticians, software engineers, and product leads — to align curation strategies with domain needs and project goals.
We would like you to have:
- BSc or MSc in a life sciences field (e.g., Biomedical Sciences, Bioinformatics, Molecular Biology).
- Strong knowledge of biomedical terminology, research data types (e.g., omics, compounds, disease models), and structured data principles.
- Familiarity with controlled vocabularies and ontologies such as MeSH, SNOMED CT, NCIt, EFO, ChEBI, Cellosaurus, etc.
- Experience working with scientific literature, protocols, or databases such as PubMed, NCBI, Ensembl, or similar.
- Strong analytical and organizational skills; comfortable working independently with complex datasets and ambiguous text.
- Excellent written English and communication skills; ability to explain terminology choices and data structuring decisions clearly.
It would be nice for you to have:
- PhD in biomedical sciences, bioinformatics, or computational biology.
- Experience in curating datasets for ML/AI applications, or reviewing model outputs for accuracy and error modes.
- Working knowledge of Python, R, or other scripting languages for data wrangling or quality control.
We offer you:
- international team of professionals;
- fully paid sick leaves;
- onboarding and domain training for newcomers;
- flexible work schedule.