ai4s-research/awesome-ai-for-science

A curated list of awesome AI tools, libraries, papers, datasets, and frameworks that accelerate scientific discovery — from physics and chemistry to biology, materials, and beyond.

What it solves

Scientific research involves complex workflows—from parsing dense PDFs and managing literature to automating data analysis and generating visual reports. This repository acts as a central hub to help researchers discover and implement AI tools that streamline these tasks, making scientific discovery faster and more reproducible.

How it works

This project is a curated, categorized directory of open-source software, datasets, and frameworks. It organizes resources into functional areas such as document parsing, research agents, data visualization, and domain-specific applications (like biology or climate science). It provides direct links to tools that researchers can integrate into their existing workflows, such as Jupyter notebooks, coding assistants, or automated document-to-data pipelines.

Who it’s for

This list is designed for researchers, data scientists, and students across all scientific disciplines who want to leverage AI to improve their productivity, automate repetitive tasks, or enhance the quality of their research outputs.

Highlights

  • Literature & Knowledge Management: Tools for searching, organizing, and synthesizing academic papers using AI.
  • Document Parsing: High-performance toolkits for converting complex scientific PDFs into machine-readable formats like Markdown or JSON.
  • Research Agents: Frameworks and skill libraries that allow AI agents to perform autonomous scientific tasks, such as protocol design or data analysis.
  • Visualization & Reporting: Automated tools for generating charts, posters, and presentation slides directly from research papers.
  • Domain-Specific Resources: Targeted collections for fields including biology, medicine, chemistry, materials science, and physics.

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