Application Guide

How to Apply for Research Scientist II

at Citrine Informatics

🏢 About Citrine Informatics

Citrine Informatics is pioneering the use of AI and data-driven approaches to accelerate the development of sustainable materials. Their platform integrates materials data, machine learning, and active learning to reduce the time and cost of bringing new materials to market. Working here means contributing to cutting-edge research that directly impacts industries from energy to electronics.

About This Role

As a Research Scientist II, you will lead funded projects that combine materials science with machine learning, from data processing to building predictive models and active learning loops. You'll manage collaborations with universities and national labs, publish scientific papers, and translate research into practical tools within Citrine's platform. This role is crucial for advancing materials informatics and driving real-world sustainability outcomes.

💡 A Day in the Life

A typical day might start with a stand-up meeting with your research team to discuss progress on a funded project, followed by coding a machine learning pipeline for a new materials dataset. You might then have a video call with collaborators at a national lab to align on data sharing, and later draft a section of a grant proposal. Afternoon could involve analyzing model results, preparing figures for a paper, or reviewing a colleague's code.

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Interview Prep

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🎯 Who Citrine Informatics Is Looking For

  • A materials scientist or chemist with a Ph.D. who has hands-on experience applying machine learning (e.g., regression, classification, optimization) to materials data, such as predicting properties or discovering new compounds.
  • Proficient in Python and familiar with libraries like scikit-learn, PyTorch, or TensorFlow, and has experience with data wrangling (e.g., pandas, NumPy) and version control (Git).
  • Demonstrates ownership of projects from conception to completion, including writing grant proposals, managing timelines, and delivering results to stakeholders.
  • Excellent communicator who can bridge the gap between domain scientists and machine learning engineers, with a strong publication record in peer-reviewed journals.

📝 Tips for Applying to Citrine Informatics

1

Tailor your resume and cover letter to highlight specific projects where you used ML to solve materials science problems, including metrics like model accuracy or time saved.

2

Mention any experience with active learning or Bayesian optimization, as these are core to Citrine's workflows.

3

If you have experience with funded research programs (e.g., DOE, NSF), explicitly describe your role in managing budgets, reporting, or collaborating with external partners.

4

Showcase your Python skills by linking to a GitHub repository with relevant code, such as a materials property prediction pipeline.

5

In your cover letter, connect your research to sustainability (e.g., developing better battery materials or catalysts) to align with Citrine's mission.

✉️ What to Emphasize in Your Cover Letter

['Emphasize your ability to lead end-to-end research projects, including data collection, model development, and deployment.', 'Highlight collaborations with diverse teams (e.g., universities, national labs) and your experience in managing technical aspects of funded programs.', 'Demonstrate your passion for applying AI to accelerate materials discovery and your understanding of sustainable materials development.', 'Provide a specific example of a machine learning model you built for a materials problem and the impact it had.']

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Explore Citrine's platform features, especially their active learning and uncertainty quantification capabilities, to understand how your work could integrate.
  • → Read recent publications from Citrine's team (e.g., on their blog or in journals like npj Computational Materials) to see their research focus.
  • → Familiarize yourself with their data ecosystem, including Citrination, and how they handle materials data standardization.
  • → Look into their partnerships with national labs (e.g., NREL, LBNL) and companies to understand the collaborative nature of funded projects.

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 Describe a project where you used active learning to optimize a material property. How did you design the acquisition function?
2 How would you handle a dataset with sparse or noisy materials data? What preprocessing or modeling strategies would you use?
3 Explain a time you had to communicate complex ML results to a non-technical stakeholder (e.g., a materials scientist).
4 How do you stay current with advances in materials informatics? Give an example of a recent paper or tool that influenced your work.
5 Tell us about a funded research program you contributed to. What was your role in writing the proposal and managing deliverables?
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⚠️ Common Mistakes to Avoid

  • Submitting a generic application that doesn't mention materials science or machine learning specifically for materials problems.
  • Downplaying your programming skills or not providing concrete examples of Python projects.
  • Failing to demonstrate an understanding of the end-to-end research lifecycle, from proposal writing to publication.

📅 Application Timeline

This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.

Typical hiring timeline:

1

Application Review

1-2 weeks

2

Initial Screening

Phone call or written assessment

3

Interviews

1-2 rounds, usually virtual

✓

Offer

Congratulations!

Ready to Apply?

Good luck with your application to Citrine Informatics!

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