Director, AI Enabled Discovery and Digital R&D
About The Position
The materials discovery cycle is being fundamentally reshaped by AI from how experiments are designed and hypotheses generated, to how results are analyzed and learning is accumulated across thousands of runs. This role owns the AI and discovery half of that transformation at EMD Electronics, leading the programs that put intelligent systems directly in the hands of R&D scientists. As part of the wider Materials AI portfolio and team, you will inherit live programs with real users and scientists already in motion, and a portfolio that has already demonstrated measurable scientific impact. The mandate is to deepen that impact, extend the AI stack to new material systems and domains, and shape what AI-enabled discovery looks like at EMD Electronics.
Requirements
- Advanced degree in computer science, data science, chemistry, materials science, or a related field
- 5+ years in technical leadership or program management in an AI/ML context within chemical R&D
- Hands-on experience with AI/ML i.e. LLMs, Bayesian optimization, or scientific ML in a real deployment context
- Demonstrated track record of building and managing collaborations with external partners, including startups, academic groups, or technology providers.
Nice To Haves
- PhD in relevant scientific or technical discipline.
- Proficiency in agentic AI architectures, LLM-based systems, and modern machine learning frameworks.
- Familiarity with Bayesian optimization, sequential learning, or computational materials science.
- Background in semiconductor or specialty chemicals R&D; understanding of R&D workflows and scientific data acquired through hands-on laboratory experience.
Responsibilities
- Define and evolve the AI-enabled discovery roadmap, aligned to the Connected → Amplified R&D phases
- Own and prioritize the AI discovery program portfolio; manage budget, delivery milestones, and TLB reporting
- Translate technology advances in AI and scientific ML into a sequenced, fundable program agenda
- Foster tight collaboration with the computational modelling and lab digitization sub-teams within Materials AI
- Develop program leads toward greater ownership and scientific ambition
- Scale a deployed multi-agent AI co-scientist from internal platform toward the primary R&D workflow tool for experiment design, documentation, and analysis
- Extend Bayesian optimization capabilities to new material systems and R&D domains; deepen sequential learning workflows and instrument data integration
- Identify and pilot emerging AI approaches, e.g., generative models, autonomous experimentation, where they create genuine scientific leverage
- Build and manage collaborations with AI startups, academic groups, and technology providers; structure engagements that bring frontier capabilities in-house
- Represent EMD Electronics' AI-for-science work externally at conferences and in strategic partnerships
- Connect relevant initiatives across Merck KGaA, Darmstadt, Germany
Benefits
- health insurance
- paid time off (PTO)
- retirement contributions
- other perquisites
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What This Job Offers
Job Type
Full-time
Career Level
Director
