Postdoc in Epistatic-Aware Machine Learning for Protein Engineering - DTU Compute

The postdoc will develop machine learning for protein engineering, including investigating epistatic effects and developing machine learning models for protein engineering. The work will be in collaboration with domain experts and will involve optimizing an NADPH-dependent enzyme called formate dehydrogenase.

Requirements

• Prior experience with machine learning from both a theoretical and practical perspective
• Experience in machine learning for protein engineering, Bayesian optimization, and uncertainty quantification
• Basic understanding of proteins and biology

Benefits

• Competitive salary
• 2-year employment contract
• Collaborative and dynamic research environment