Head of AI Research

DUDE CHEM; Berlin; Hybrid; EUR 150.000 - 190.000; Vollzeit

Zusammenfassung

Dunia seeks a Head of AI Research to define and lead the AI-for-Materials agenda at the intersection of ML, physics, chemistry, and automated experimentation. You will invent representations, learning paradigms, and evaluation frameworks for AI to reason about matter across scales and build scalable discovery platforms.

You will spearhead the Materials World Model, shaping how AI interacts with experiments and simulations, and ensure models are grounded in physical reality with experimental

Qualifikationen

• PhD in ML; background in physics, chemistry, or related field desired.
• 7+ years of AI research experience with leadership of senior ICs.
• Deep experience in representation learning, scientific ML, or foundation models.
• Strong intuition for physical systems and their constraints.
• Proven ability to operate at the boundary between theory, systems, and real-world feedback.
• High scientific taste and comfort making irreversible prioritization decisions under uncertainty.
• Clear communicator who can align researchers, engineers, and leadership around ambitious goals.

Aufgaben

• Set the intellectual direction for AI for Materials.
• Build and lead a world-class research team.
• Turn research into systems that discover through end-to-end discovery loops.
• Shape the external field and collaborations across academia and industry to advance the field.

Kenntnisse

PhD in ML

7+ years AI research

Representation learning

Scientific ML

Foundation models

Physical intuition

Clear communicator

Ausbildung

PhD in ML; physics/chemistry background desired

Jobbeschreibung

Your mission

Define how AI can understand, reason about, and discover materials
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 Head of AI Research, you will define and lead Dunia’s AI-for-Materials agenda at the intersection of machine learning, physics, chemistry, and automated experimentation. This role is about more than applying existing ML techniques to scientific data. It is about inventing the representations, learning paradigms, and evaluation frameworks that allow AI to reason about matter across scales.

You will spearhead the development of Dunia's Materials World Model, shaping how AI interacts with experiments and simulations, and how scientific insight is translated into systems that reliably produce new materials with real-world impact.

Your tasks will include:

Set the intellectual direction for AI for Materials

• Define Dunia’s research thesis for AI-native materials discovery
• Identify where existing ML paradigms fail when applied to physical matter, and what must be built instead
• Decide which research bets have the potential to shift the field, not just improve benchmarks

Build and lead a world-class research team

• Hire, mentor, and challenge senior ML researchers and scientists
• Create an environment that values deep thinking, honest evaluation, and intellectual courage
• Set a high bar for scientific taste, clarity, and originality

Turn research into systems that discover

• Work closely with Programs, Hardware & Automation, and Software Architecture to embed research into end-to-end discovery loops
• Ensure models are grounded in physical reality and experimental feedback, not just data abstractions
• Balance long-horizon research with near-term delivery without reducing ambition

Shape the external field

• Influence how AI for Materials is discussed, evaluated, and pursued across academia and industry
• Build collaborations that extend Dunia’s reach while protecting focus and IP
• Represent a clear, opinionated point of view on where the field should go next

Your profile

• PhD in ML; background in physics, chemistry, or a related field desired
• 7+year's experiencein AI research, including leadership of senior ICs
• Deep experience in representation learning, scientific ML, or foundation models
• Strong intuition for physical systems and their constraints
• Proven ability tooperateat the boundary between theory, systems, and real-world feedback
• High scientific taste and comfort making irreversible prioritization decisions under uncertainty
• Clear communicator who can align researchers, engineers, and leadership around ambitious goals
• English fluency,additionallanguages preferred