Lila Sciences

1 month ago

Co-Op, Data Extraction

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Job Summary

Data Extraction Co-Op at Lila Sciences supports building AI systems that convert unstructured scientific knowledge into structured signals. You will fine-tune and evaluate extraction models, develop pipelines for messy data across text, tables, and visuals, run extraction workflows, and communicate results to the team, contributing to production-ready research outputs.

Location: Cambridge

Workplace: Onsite

Employment Type: Internship

Job Function: Data Analytics & Business Intelligence

Seniority: Intern level

Key Responsibilities

•Collaborate with researchers and engineers to extract and structure knowledge from scientific literature and patents
•Fine-tune and evaluate language, multimodal, or specialized models for data extraction under mentorship
•Build and test pipelines to structure unstructured scientific data across text, tables, and visuals
•Run extraction pipelines, analyze results, and document findings clearly for team consumption
•Share your work through presentations, write-ups, or contributions to publications/open-source projects

Key Requirements

•Pursuing a Bachelor's, Master's, or PhD in Computer Science, Chemistry, Materials Science, or a related field
•Solid foundation in machine learning fundamentals and Python
•Familiarity with NLP or computer vision concepts
•Curiosity about scientific data and willingness to learn quickly in a research setting
•Bonus points for coursework or projects involving multimodal models or document understanding (OCR, table/figure extraction) or experience with messy real-world datasets

Education:Bachelor's in Computer Science

Skills:PythonNLPComputer visionOCRMultimodal models

Languages:English

Tech Stack:PythonNLPComputer visionOCRMultimodal models

Company Brief

Lila Sciences

Develops AI-driven platforms to accelerate drug discovery and biological research by integrating machine learning with chemical and biological data to predict molecular properties, streamline candidate selection, and enable faster therapeutic development.

Industry: Biotech

Company Size: Small (11 to 50 employees)

Growth: Early Stage Startup

Funding: Seed

Website LinkedIn

Loading job details...

Preparing the role view and application actions.

Lila Sciences

1 month ago

Co-Op, Data Extraction

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Job Summary

Location: Cambridge

Workplace: Onsite

Employment Type: Internship

Job Function: Data Analytics & Business Intelligence

Seniority: Intern level

Key Responsibilities

•Collaborate with researchers and engineers to extract and structure knowledge from scientific literature and patents
•Fine-tune and evaluate language, multimodal, or specialized models for data extraction under mentorship
•Build and test pipelines to structure unstructured scientific data across text, tables, and visuals
•Run extraction pipelines, analyze results, and document findings clearly for team consumption
•Share your work through presentations, write-ups, or contributions to publications/open-source projects

Key Requirements

•Pursuing a Bachelor's, Master's, or PhD in Computer Science, Chemistry, Materials Science, or a related field
•Solid foundation in machine learning fundamentals and Python
•Familiarity with NLP or computer vision concepts
•Curiosity about scientific data and willingness to learn quickly in a research setting
•Bonus points for coursework or projects involving multimodal models or document understanding (OCR, table/figure extraction) or experience with messy real-world datasets

Education:Bachelor's in Computer Science

Skills:PythonNLPComputer visionOCRMultimodal models

Languages:English

Tech Stack:PythonNLPComputer visionOCRMultimodal models

Company Brief

Lila Sciences

Industry: Biotech

Company Size: Small (11 to 50 employees)

Growth: Early Stage Startup

Funding: Seed

Website LinkedIn