Industry Postdoc: Enzymatic catalysis

 

Dayhoff Labs invites applications for a postdoctoral position focused on validating machine learning model predictions through experiments. The role includes working with high throughput assays to produce datasets that help improve and refine Dayhoff’s models. The selected candidate will utilize these models for scientific research, blending experimental work with computational modeling.

 

Responsibilities:​

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• Collaborate closely with a AI researchers, computational biologists and protein biochemists to advance understanding in enzyme biochemistry and machine learning.

• Conduct experimental validation to test evolutionary hypotheses inspired by model predictions and generate data for machine learning model training.

• Design and build new datasets essential for machine learning model development.

• Apply machine learning and AI methodologies to investigate enzyme functions in novel chemical contexts, including new-to-nature chemistry and ancient extinct reactions.

• Contribute to the development of innovative approaches for integrating experimental data with computational predictions.

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Requirements:​

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• Ph.D. in Biochemistry, Molecular Biology, or a related field.

• Expertise in protein purification, heterologous expression, in vitro biochemical assays, and analytical chemistry techniques.

• Direct experience with analytical techniques such as HPLC, GC/MS, LC/MS and spectroscopy. 

• Excellent communication and collaboration skills.

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This position is based out of the Earth and Life Science Institute in Tokyo, Japan, under the supervision of Professor Liam Longo. To apply, please submit your resume and a cover letter outlining your experience and suitability for the role to careers@dayhofflabs.com