Materials Informatics Scientist (Evaluation-focused)

Dunia; Berlin; Vor Ort; EUR 70.000 - 90.000; Vollzeit

Zusammenfassung

A global clean energy innovator in Berlin is seeking a Materials Informatics Scientist to evaluate and validate AI models for materials discovery. This role requires a PhD or Master's degree in a relevant field and significant experience in scientific systems under uncertainty. The successful candidate will develop evaluation frameworks, benchmark models, and communicate findings to ensure a clear understanding of model performance. Join a diverse workplace dedicated to impactful clean energy solutions.

Qualifikationen

• PhD strongly preferred or Master's degree in materials science, chemistry, or related fields.
• 5–8 years of experience with scientific or ML systems.
• Experience evaluating, benchmarking, or validating models.

Aufgaben

• Own evaluation as a scientific discipline for AI models.
• Interrogate and compare models across training regimes.
• Communicate findings clearly to researchers and leadership.

Kenntnisse

Programming skills in Python

Experience with scientific data tooling

Understanding of materials science

Fluency in English

Ausbildung

PhD or Master’s degree in a relevant field

Jobbeschreibung

Your mission

Define how AI models for materials discovery are evaluated, compared, and trusted

Dunia is building AI for one of the hardest unsolved problems in science: turning materials discovery from an academic, trial-and-error process into a programmable, scalable discipline.

As our models grow more complex and our experimental throughput increases, the limiting factor is no longer generating predictions, but knowing which ones to believe.

As Materials Informatics Scientist (Evaluation-focused), you will own the evaluation and validation of AI models applied to materials discovery. Your role is to ensure that model performance claims are meaningful, comparable, and decision-relevant, and that progress in AI for Materials reflects real improvements in discovery, not artifacts of metrics or datasets.

This role is not about building new models. It is about defining the standards by which models are judged.

Your tasks

• Own evaluation as a scientific discipline
  • Design, implement, and maintain evaluation frameworks for AI models across materials discovery tasks
  • Define metrics and protocols that reflect generalization, robustness, uncertainty, and experimental relevance
  • Identify failure modes, dataset leakage, and misleading performance signals

• Interrogate and compare models
  • Systematically benchmark different model classes, training regimes, and representations
  • Evaluate tradeoffs between accuracy, uncertainty, data efficiency, and usability
  • Provide clear, defensible recommendations on which models to trust, deploy, or retire

• Connect AI performance to real outcomes
  • Link model behavior to experimental results and program-level objectives
  • Distinguish improvements that change decisions from those that only improve abstract scores
  • Help research and programs teams understand what current models can and cannot reliably do

• Build robust analytical tooling
  • Develop and maintain professional-grade scripts and analysis pipelines for evaluation and benchmarking
  • Visualize complex, high-dimensional results in ways that surface real insight
  • Ensure disciplined, reproducible handling of data, code, and results

• Communicate truth clearly
  • Present findings clearly to AI researchers, materials scientists, and leadership
  • Produce concise summaries that align the organization around a shared view of evidence and uncertainty
  • Act as an independent scientific reference point when claims require validation

Your profile

• PhD (strongly preferred) or Master’s degree in materials science, chemistry, physics, machine learning, or a related field
• Significant experience (typically 5–8 years) working with scientific or ML systems under real-world uncertainty
• Demonstrated experience evaluating, benchmarking, or validating models rather than only building them
• Strong programming skills in Python and scientific data tooling
• Deep appreciation for rigor, reproducibility, and careful interpretation of results
• English fluency, additional languages preferred

About us

Dunia, meaning “world” in over 20 languages, reflects our global mission: to drive clean energy innovation in the hardest-to-decarbonize sectors. With cutting-edge physics AI technology, we’re accelerating breakthroughs in materials science to help reduce global CO2 emissions by billions of tons annually. Join us and make a real difference in a dynamic, impact-driven environment.

We strive to create a diverse and inclusive workplace where everyone feels welcome and safe to be their authentic self. Non-traditional career paths are welcome and valued. If you share our vision, you can be certain that we want you to succeed. You might be just the right candidate for this or for other roles that have not opened yet. Reach out!