Bayer·1 month ago
1 month ago
Data Scientist / PostDoc - Machine Learning & Profile - Driven Enzyme Discovery
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What you'll do
- 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.
What they're looking for
- 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 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
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
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. 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 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. LI-DE | ---|--- YOUR APPLICATION| | 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.
Company
Bayer
Monheim, Germany
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