Materials Informatics Acceleration Program
Helping innovation-driven organizations build internal digital R&D capabilities so that they can make better, faster decisions in the lab and bring new innovative products to market faster than ever before.
Materials and Chemical Innovation Challenges
Companies that synthesize, formulate, process, and integrate advanced materials and chemicals into their products are facing heightened innovation pressures — and opportunities. Historically high-margin specialty products are becoming more commoditized, and the race is on for companies to differentiate themselves in existing markets and establish a leading presence in new emerging markets.
Industry success now more than ever is being dictated by the ability to continuously develop and/or leverage innovative new materials and chemicals.
Building the Lab of the Future Now
Business and R&D leaders both envision modern data science tools and methods as part of the solution to their innovation needs, but most organizations lack R&D staff with the right combination of domain expertise and the digital skills required to conceive, manage, and implement data-driven projects.
To find success, companies are actively investing in materials informatics (MI), the intersection of materials/chemicals and data science.
Materials Informatics Acceleration Program
For over 20 years, Enthought has been developing powerful scientific software solutions and helping innovation-driven organizations build internal digital R&D capabilities — all towards making better, faster decisions in the lab and bringing new innovative products to market faster than ever before.
Through Enthought’s unique Materials Informatics Acceleration Program, our world-class team of training and MI experts work alongside in-house scientists and engineers to leverage the wealth of tools in the scientific computing ecosystem and to develop tailored scientific software solutions.
Elevate Your Team and Your Capacity
With Enthought’s guided partnership, companies will:
- Develop in-house MI capabilities by tackling real in-house challenges
- Craft MI solutions that will start generating immediate value
- Identify and cultivate future digital R&D leaders
- Create a community of practice to catalyze broader digital culture change
Partner with Enthought Scientists and Developers
The 3 key components of the MI Acceleration Program are:
- Discovery – Scope out potential solutions to real challenges and focus efforts on tractable problems that can generate real value
- Classroom Training – Curated Python, machine learning, and MI training courses to start solving real problems faster
- Apprenticeship Projects – Collaborate with Enthought MI experts to rapidly develop solutions to real problems
Contact us to learn more about each component.
Imagine the Possibilities
Through the MI Acceleration Program, your team could:
- Create a data-driven experiment recommendation tool for rapid optimization of complex synthesis, formulation, processing, or selection challenges to reduce wasted experiments and reach design objectives much faster
- Automate data analysis pipelines for raw data (spectra, images, curves, etc.) to reduce human bias and accelerate experimental and/or computational iterations
- Quantify the cost and value of the different data sources needed to predict critical performance metrics to help prioritize future data gathering and automation efforts
- Augment sparse datasets with physics-based simulations and open datasets to get the most out of your existing data and expertise
Time to Invest in Your R&D Team
Fill out the form below to connect to one of our MI experts today.
Meet Our Materials Informatics Experts
The Enthought MI team has a wide range of expertise including Graph Neural Networks, Bayesian Optimization, Deep Learning, GAN, NLP, Open Data, MD, DFT, Multi-scale Modeling, Electrochemical Simulation, Mathematical Modeling, Molecular Representation, Cloud, Databases, Data Pipelines, Data Ops, ML Ops, Web and Desktop UIs.
Michael Heiber
Director, Professional Services & Customer Success, Materials Informatics
Shohei Ogawa
Scientific Software Developer
Nathan Wilson
Scientific Software Developer