Postdoctoral Chemical Data Scientist
We are seeking a highly motivated and skilled Postdoctoral Fellow in Chemical Data Science to join a new collaborative research project that aims to create an intelligent automated synthesis platform, incorporating reaction outcome prediction methodology and standardized synthesis automation.
Project Overview
The project brings together the expertise of Professor Jeffrey Bode's group at ETH Zurich and Synple Chem in Kemptthal, Zürich, to improve and expand Synple Chem's existing synthesis automation platform by increasing throughput and improving its self-learning nature.
The successful candidate will contribute to the development of a system for automating and accelerating hit discovery in pharmaceutical research, working closely with synthetic chemists to tightly couple synthetic predictions and reaction automation.
Key Responsibilities
* Collaborate with synthetic chemists to optimize reaction conditions and generate data for building effective AI/ML models for predicting reaction outcomes
* Develop and apply innovative active-learning strategies to support reaction optimization and implementation of automation-friendly protocols
* Capture, manage, query, and explore experimental data generated during reaction optimizations computationally
* Expand and refine existing pipelines for defining, enumerating, and screening virtual libraries based on optimized reactions and available building blocks
* Develop approaches to rapidly include new reaction classes into predictive models and automation protocols
Requirements
* PhD in chemistry, data science, or a related field
* Extensive experience with cheminformatics
* Software development skills
* Solid understanding of organic chemistry and chemical processes
* Experience with modern AI/ML approaches
* Understanding of basic automation techniques, databases, and data analysis tools
* Excellent written and verbal communication skills (English)
We Offer
* Opportunity to conduct research at the interfaces of several hot fields: AI-assisted drug discovery, virtual screening, and automated synthesis
* Collaborative work with both synthetic and computational chemists from academic research groups and industry
* An applied research project with high-impact scientific and commercial goals
* A highly supportive, multidisciplinary team environment
In line with our values, ETH Zurich encourages an inclusive culture, promoting equality of opportunity, valuing diversity, and nurturing a working and learning environment where the rights and dignity of all staff and students are respected.