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

Bayer AG
Monheim am Rhein, Germany
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English

Tech stack

Computational Biology Machine Learning Deep Learning Optimization Algorithms Programming Languages

Job description

  • 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.

Requirements

  • 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.

Benefits & conditions

Bayer offers a wide variety of competitive compensation and benefits programs. If you meet the requirements of this unique opportunity, and want to impact our mission Health for all, Hunger for none, we encourage you to apply now. Be part of something bigger. Be you. Be Bayer.

About the company

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., 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. Equal Opportunity Employer Statement: Notice for U.S. Visitors: All information on this site is subject to compliance with local rule and regulations as they may vary from time to time and across different geographies, including, without limitation, U.S. Executive Orders.

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