The Nevado Group at the University of Zurich in collaboration with Teodoro Laino’s team at IBM Research is looking for a postdoctoral researcher in Machine Learning and Chemistry to develop tools for the design and optimization of cross-coupling reactions relevant in medicinal chemistry.This position is funded by the NCCR Catalysis: The National Center of Competence in Research NCCR Catalysis aims to develop skills, tools, and technologies that facilitate the transition toward a carbon-neutral and waste-free chemical industry. The network, in operation since 2020, is funded by the Swiss National Science Foundation and currently comprises ten universities, two research institutes and an industrial partnership with over 200 members.
The successful candidate will join a highly interdisciplinary team involving medicinal chemists and computational scientists to work on the development of ML models that will help experimental groups to attain efficient cross-coupling reactions for highly tailored and structurally challenging building blocks that are typically not covered in the literature. Existing data-driven approaches, such as models predicting yields or experimental conditions will be applied to meet the project goals. Additionally, the appointed person is expected to analyze the strengths and weaknesses of these approaches and propose complementary data-driven models to help in the design of improved conditions for these challenging transformations. The successful candidate will also closely collaborate with experimental colleagues to propose new experiments that will benefit the development and reliability of the data-driven models in an active-learning setting. The postdoctoral researcher will be exposed to the experimental activities of the Nevado Group and will also be in regular exchange with collaborators from IBM Research to identify and implement data-driven approaches with direct impact on synthesis works.
- PhD in computer science, computational chemistry, or a related field
- Experience in data collection and data processing and prior expertise in machine learning (TensorFlow, Keras, PyTorch, transformers, …)
- Advanced programming skills, as well as proficiency in common Python libraries (pandas, sklearn, …)
- Knowledge and/or experience in organic/organometallic chemistry is a plus
- Excellent interpersonal skills and curiosity-driven mindset
- Creative, proactive, and problem-solving attitude
We seek an enthusiastic individual with the ability to work both highly independent as well as in a team. In addition to relevant experience in the abovementioned activities, the candidate should have excellent project management and communication skills and be fluent in English. The candidate should have received their PhD within the last 12 months or not have more than two years of previous post-doctoral experience. Applications of senior researchers or senior post-docs will not be considered.
What we offer
Our well-funded research program combines inspiring international research environment with access to state-of-the-art scientific infrastructure. Our alumni value their comprehensive training: about 25% of them are offered a tenure track assistant professorship position, with the vast majority of the rest finding employment in large pharma or biotech industry.
Place of work
Start of employment
Employment starting date will be mutually agreed upon (preferably as soon as possible).We ask strongly motivated candidates to submit their applications containing a motivation letter, a research summary of past accomplishments (2 pages), a CV (resumé), and 1 letter of support (or the names and contact details of 2 referees) in a single pdf file.