Postdoctoral Chemical Data Scientist

vor 3 Wochen

Zürich, Zürich, Schweiz Eidgenössische Technische Hochschule Zürich Vollzeit

We are seeking a highly motivated and skilled Postdoctoral Fellow in Chemical Data Science to join a new Innosuisse-funded collaborative research project that seeks to create an intelligent automated synthesis platform, incorporating reaction outcome prediction methodology and standardized synthesis automation. The successful candidate will be supported by, and work collaboratively with Professor Jeffrey Bode at the ETH in Zürich and Synple Chem in Kemptthal, Zürich. They will work closely with other researchers within the Bode group and the wider ETH community, as well as the Synple Chem team.

Project background

The overarching goal of this project is to bring together the Bode group's broad expertise in synthesis and reaction outcome prediction, and Synple Chem's synthesis automation, to improve and expand Synple Chem's existing synthesis automation platform by increasing throughput and improving the self-learning nature of the platform. The project will provide the opportunity to be involved with cutting-edge research across the fields of organic synthesis, chemistry automation, reaction informatics, and machine learning. The successful candidate will contribute to our development of a system for automating and accelerating hit discovery in pharmaceutical research.

The successful candidate will collaborate with synthetic chemists to tightly couple synthetic predictions and reaction automation. Some possible research topics include:

  • Collaborations with synthetic chemists to optimize reaction conditions and generate the data to build effective AI/ML models for predicting whether a particular set of building blocks will work in a reaction
  • Developing and applying innovative new active-learning strategies to support reaction optimization and the implementation of automation-friendly protocols
  • Developing new systems for capturing, managing, querying, and exploring the experimental data generated during the reaction optimizations computational
  • Expanding and refining existing pipelines for defining, enumerating, and screening virtual libraries based on the optimized reactions and available building blocks
  • Developing approaches to allow the rapid inclusion of new reaction classes into the predictive models and automation protocols
Profile
  • PhD in chemistry, data science, or a related field
  • Extensive experience with Cheminformatics
  • Experience with software development
  • 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
  • Working collaboratively 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. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish.

Curious? So are we.

We look forward to receiving your application with the following documents:

  • Detailed CV
  • Transcripts of all degrees including ranking information (English)
  • Names and contact information of at least three references
  • Representative published research work (Papers, thesis if possible)

Please submit the application documents using only the ETH online portal in a single merged PDF document, titled with your last name and initials as well as the application date (for example, name_application). Do not send it by e-mail, LinkedIn, etc.

Questions regarding the position should be directed to Prof. Jeffrey Bode, by email at bode@org.chem.ethz.ch.

We evaluate applications on a rolling basis.

ETH Zurich is one of the world's leading universities specializing in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.

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