Global Breeding Innovation & Acceleration Lead

Bayer

Rojas

Hybrid

ARS 227.183.000 - 287.765.000

Vollzeit

Vor 4 Tagen
Sei unter den ersten Bewerbenden

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Zusammenfassung

Bayer is seeking a Research and Impact Acceleration Lead to define the vision and multi-year plan for accelerating research across the early breeding pipeline. You will drive improvements in speed, evidence quality, and genetic gain, partnering with global teams to deliver faster, higher-quality products for growers and customers worldwide.

You will shape the enabling technology agenda, govern adoption strategies, and influence leadership decisions through robust metrics and an evidence-based

Qualifikationen

  • PhD/MS in Plant/Animal Breeding, Quantitative or Statistical Genetics, Data Science, or related field.
  • Strong knowledge of advanced breeding technologies, analytics, genomics, or quantitative genetics with a track record of applying to pipelines.
  • Ability to collaborate across regions and functions to solve complex problems.

Aufgaben

  • Define the multi-year strategy for research acceleration in the early breeding pipeline.
  • Set standards for hypothesis-driven design and evidence to enable rapid iteration.
  • Lead enabling-technology agenda across accelerated breeding, genomics, phenotyping, and digital workflows.

Kenntnisse

Cross-functional collaboration
Stakeholder influence
Strong communication

Ausbildung

PhD in Plant/Animal Breeding or related
MS in related field

Tools

Genomics platforms
Phenotyping tools
Predictive analytics

Jobbeschreibung

Bayer is seeking a Research and Impact Acceleration Lead to define the vision and multi-year plan for accelerating research across the early breeding pipeline. You will drive improvements in speed, evidence quality, and genetic gain, partnering with global teams to deliver faster, higher-quality products for growers and customers worldwide.

You will shape the enabling technology agenda, govern adoption strategies, and influence leadership decisions through robust metrics and an evidence-based

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