Data Scientist / PostDoc - Machine Learning & Profile - Driven Enzyme Discovery

Bayer CropScience Limited; Monheim am Rhein; Vor Ort; EUR 70.000 - 100.000; Vollzeit

Zusammenfassung

Bayer CropScience Limited in Monheim, Germany is seeking a Data Scientist / PostDoc focused on machine learning driven enzyme discovery. You will connect probabilistic modeling with design of experiments to unlock novel enzyme variants for high-impact pipeline applications.

The role spans cross-divisional work with Pharma and Crop Science R&D, translating complex models into actionable insights for lab and business decisions, within Bayer’s Life Science Collaboration framework.

Qualifikationen

• PhD in machine learning or highly quantitative discipline
• Deep theoretical and practical expertise in advanced ML, probabilistic modeling, optimization, active learning

Aufgaben

• Develop and deploy active learning loops to explore sequence spaces and discover informative variants for lab testing.
• Build multi-objective optimization models to meet complex performance profiles for enzymes.
• Implement predictive ML models using protein representation learning to relate sequence-structure-function for insights.
• Collaborate with data experts and wet-lab scientists to test hypotheses and interpret DoE results.
• Drive methodological innovations and translate probabilistic models into actionable R&D strategies for leadership.

Jobbeschreibung

At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where 'Health for all Hunger for none’ is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining ‘impossible’. There are so many reasons to join us. If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice.

Data Scientist / PostDoc - Machine Learning & Profile - Driven Enzyme Discovery

We are seeking a highly skilled and motivated Research Scientist to join our interdisciplinary R&D team in Monheim, Germany, focused on machine learning-driven discovery and profile-driven enzyme design. In this role, you will help advance industrial protein design by connecting probabilistic modeling, sequence-to-function predictions, design of experiments, and active learning to unlock novel protein variants for high-impact pipeline applications.

The successful applicant will work in a cross-divisional environment across Pharma and Crop Science R&D, contributing to state-of-the-art research while translating complex computational approaches into practical scientific impact.

YOUR TASKS AND RESPONSIBILITIES

• Develop and deploy active learning loops and probabilistic optimization strategies to explore vast, unknown sequence spaces and drive the discovery of highly informative variants for lab testing.
• Build multi-objective optimization models capable of discovering entirely new enzymes that simultaneously meet complex performance profiles.
• Implement predictive machine learning models, leveraging state-of-the-art protein representation learning to capture deep sequence-structure-function relationships and uncover novel biological insights.
• Collaborate closely with scientific data experts to leverage complex knowledge graphs, and work with wet-lab scientists to evaluate model-generated hypotheses and interpret Design of Experiments (DoE) results.
• Drive methodological innovation and translate highly complex probabilistic models and algorithmic discoveries into clear business impacts, risk assessments, and R&D strategies for executive leadership.

WHO YOU ARE

• You hold a PhD in machine learning, computational biology, physics, mathematics, or a highly quantitative discipline.
• You bring deep theoretical and practical expertise in advanced machine learning, specifically probabilistic modeling, optimization algorithms, and active learning strategies geared towards scientific discovery.
• You have a solid grasp of protein chemistry and mutational effects, ensuring that ML-generated predictions are biologically plausible and translate into actionable discoveries for the wet lab.
• You actively challenge the status quo, relentlessly pursuing methodological innovation to solve complex, noisy biological problems and uncover new mechanisms in novel ways.
• You possess strong collaboration strategies, successfully orchestrating the 'Closed Loop' process by seamlessly bridging algorithmic hypothesis generation, wet-lab execution, and model refinement.
• You are proficient in modern programming languages and the standard ecosystems for deep learning and probabilistic modeling.
• You communicate clearly in English, both verbally and in writing, and can distill complex probabilistic concepts and scientific discoveries into strategic insights for cross-functional teams and leadership.

Position Context

This two-year limited position is firmly embedded within the Bayer Life Science Collaboration (LSC) framework—Bayer’s premier cross-divisional innovation platform. Operating specifically within this framework over a defined 24-month timeline, you will leverage its unique ecosystem to drive breakthrough R&D innovation through scientific collaboration, knowledge exchange, and rapid experimentation across Pharmaceuticals, Crop Science, and Consumer Health.

The LSC framework is designed to bring together diverse talents and disciplines. By working within this collaborative structure, you will have the platform and resources to address strategic R&D challenges, develop pipeline-enabling solutions, and accelerate the translation of novel, data-driven ideas into tangible impact for patients, farmers, and consumers.

Bayer offers a wide variety of competitive compensation and benefits programs.

To all recruitment agencies: Bayer does not accept unsolicited third party resumes.

Bayer is an Equal Opportunity Employer/Disabled/Veterans

Bayer is committed to providing access and reasonable accommodations in its application process for individuals with disabilities and encourages applicants with disabilities to request any needed accommodation(s) using the contact information below.

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Bayer is an E-Verify Employer.

Location: Deutschland : Nordrhein-Westfalen : Monheim

Division: Crop Science

Reference Code: 879288

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