About the role#
As a Data Extraction Co-Op at Lila Sciences, you will work alongside research scientists and engineers to turn unstructured scientific knowledge, such as literature, patents, and technical reports, into structured data. You will focus on a specific sub-problem within the extraction stack, gaining hands-on experience by fine-tuning models and building pipelines that feed into production systems.
What you'll do#
- Contribute to AI systems that extract and structure knowledge from scientific literature and patents.
- Fine-tune and evaluate language, multimodal, or specialized models for data extraction with mentor guidance.
- Build and test pipelines to structure unstructured scientific data found in text, tables, and visuals.
- Run extraction pipelines, analyze results, and document your findings clearly.
- Share your work through team presentations, written reports, or contributions to publications or open-source projects.
What you'll need#
- Currently pursuing a Bachelor's, Master's, or PhD in Computer Science, Chemistry, Materials Science, or a related field.
- A solid foundation in machine learning fundamentals and Python.
- Familiarity with natural language processing (NLP) or computer vision concepts.
- Curiosity about scientific data and a willingness to learn in a research environment.
- Preferred: Coursework or projects involving multimodal models or document understanding, such as OCR or table/figure extraction.
Location & details#
- Location: Cambridge, Massachusetts.
- Modality: On-site.
- Employment: Full-time, paid position.
- Term: Rolling.
