Skip to content

Materials Informatics Scientist

Materials Informatics Scientists use ML to discover new materials and compounds. They combine chemistry, physics, and data science for materials innovation.

Median Salary

$175,000

Job Growth

Emerging — materials discovery using AI growing

Experience Level

Entry to Leadership

Salary Progression

Experience LevelAnnual Salary
Entry Level$110,000
Mid-Level (5-8 years)$175,000
Senior (8-12 years)$240,000
Leadership / Principal$310,000+

What Does a Materials Informatics Scientist Do?

Materials Informatics Scientists use machine learning and computational chemistry to discover and design new materials with desired properties. They run quantum simulations (DFT) to compute material properties, build ML models that predict properties without simulation, design new candidate materials using ML, validate predictions experimentally, and accelerate materials discovery cycles. They work in emerging materials science and energy storage companies.

A Typical Day

1

Simulation: Run DFT calculations predicting crystal structure and electronic properties

2

Feature engineering: Create features from atomic structure for ML models

3

Model training: Train graph neural network predicting material properties

4

Validation: Compare model predictions against DFT and experimental data

5

Exploration: Use model to identify promising new materials with desired properties

6

Synthesis planning: Collaborate with experimentalists on synthesis and testing

7

Analysis: Analyze relationship between composition/structure and properties

Key Skills

DFT calculations
Graph neural networks
Matminer
Python
Materials databases
Chemistry knowledge

Career Progression

Materials informatics scientists lead materials discovery programs. May become Director of Materials Research or Chief Scientist at materials companies.

How to Get Started

1

Learn chemistry and physics: Strong foundation in materials science

2

DFT: Learn to run quantum mechanical simulations (VASP, Quantum ESPRESSO)

3

ML for materials: Study machine learning for materials science

4

Graph neural networks: Learn GNNs for atomic structure data

5

Matminer: Use Matminer library for materials data and feature extraction

6

Research: Work in materials chemistry or physics lab

Frequently Asked Questions

What does materials informatics do?

Uses computational and ML methods to design and discover new materials. Accelerates materials development from years to months.

What's DFT?

Density Functional Theory. Quantum mechanical simulation of materials at atomic level. Predicts properties without synthesis.

Why use ML?

DFT expensive computationally. ML learns from simulation results, predicts properties for new materials instantly.

What applications exist?

Batteries (energy storage), catalysts (chemical reactions), semiconductors, superconductors, structural materials, solar cells.

Where do they work?

Research labs at materials companies, battery startups, semiconductor companies, national labs, universities.

Ready to Apply? Use HireKit's Free Tools

AI-powered job search tools for Materials Informatics Scientist

hirekit.co — AI-powered job search platform

Last updated: 2026-03-07