NLP Data Scientist / Scientific Data EngineerEuropean Bioinformatics Institute (EMBL-EBI) • Hartford, England, United Kingdom
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NLP Data Scientist / Scientific Data Engineer
European Bioinformatics Institute (EMBL-EBI)
- Hartford, England, United Kingdom
- Hartford, England, United Kingdom
À propos
Responsibilities
Develop machine learning pipelines for extracting drug side effects from drug labels, clinical trials, publications and other documents
Investigate modern NLP methodologies and propose ideas for the implementation of data extraction methods and pipelines
Apply language models to extract and map drug-related information from unstructured text, e.g. from the scientific literature, ClinicalTrials.gov
Implement and/or fine‑tune different NLP models, e.g. NER models, transformer models, LLMs
Integrate project workflows with existing infrastructures in the EBI Chemical Biology Services and Open Targets teams
Prepare and evaluate benchmark datasets from the open domain as training sets for NLP models
Work with domain experts to develop new gold standards for NLP tasks where needed
Assist with and/or perform data curation to prepare clean and reliable training sets
Apply and/or adapt existing methods for mapping extracted entities to biomedical ontologies, e.g. drugs, side effects/phenotypes, and diseases
Work closely with Safety 2.0 project group members bridging the ChEMBL and Open Targets teams
Work closely with the Open Targets Core team to ensure seamless integration of data and workflows into the Open Targets Platform and long‑term sustainability
Collaborate with the Open Targets Partners to assess, prioritise, validate and refine the developed methods
Disseminate the outcomes of the project to the scientific community and stakeholders through presentations and publications
Qualifications
PhD, Masters or equivalent experience in computational linguistics, computer science, bioinformatics, or cheminformatics
Experience with language models e.g. transformer models, LLMs, AI agents for information extraction
Experience with document and text preprocessing, cleaning and transformation techniques including mapping to ontologies
Experience with data structures, data models and databases
Knowledge of cheminformatics resources and/or bioinformatics databases
Knowledge of data analysis and machine learning
Proficiency in Python
Knowledge of data frameworks e.g. pySpark, pandas, Polar
Excellent attention to detail
Strong communication skills, both presentations and verbal
Experience working in a team‑oriented environment and collaborating
Able to work independently, to manage time and work to deadlines
Preferred Experience
Experience with the application of NLP methods to cheminformatics and/or biomedical domains
Experience with version control
Experience in safety/toxicology in industry or research
Location, Contract & Salary Open at EMBL‑EBI, Cambridge, United Kingdom. Contract length : 3 years (project based). Salary : Grade 5‑6 (monthly £3 303‑£3 695 after tax, excluding pension & insurances). Closing date : 11 / 01 / 2026. Hybrid Working : At EMBL‑EBI we embrace a hybrid approach – team members are typically on site at least three days a week, with a desk always available.
Interview Process Introductory meetings will be held remotely starting in February 2026.
Why Join Us EMBL‑EBI, part of the European Molecular Biology Laboratory, is a world‑leading research centre for large biological data. Enjoy a collaborative, inclusive culture, flexible working and a wide range of on‑site and remote facilities.
Benefits
Financial incentives : monthly family, child and non‑resident allowances, annual salary review, pension scheme, death benefit, long‑term care, accident‑at‑work and unemployment insurances
Flexible working arrangements – including hybrid patterns
Private medical insurance for you and your immediate family (including prescriptions, dental and optical cover)
Generous time off : 30 days annual leave per year plus public holidays
Relocation package including installation grant (if required)
Campus life : free shuttle bus, on‑site library, subsidised gym and cafeteria, casual dress code, sports and social club activities (on campus or remotely)
Family benefits : on‑site nursery, 10 days child sick leave, generous parental leave, holiday clubs on campus and monthly family and child allowances
Benefits for non‑UK residents : visa exemption, education grant for private schooling, financial support to travel back home every second year and a monthly non‑resident allowance
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Compétences linguistiques
- English
Avis aux utilisateurs
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