Winner: 2021 Harrison-Meldola Memorial Prize
Professor Fernanda Duarte
University of Oxford
For introducing multidisciplinary approaches to rationalise complex (bio)chemical reaction mechanisms, guiding rational molecular design.

The discovery of new molecules is crucial to modern societies. However, the process of transforming molecular sketches into real applications, such as new types of batteries or drugs, is often slow and expensive, requiring many expert scientists and hours of work. As computational chemists, Professor Duarte’s team use computers as 'molecular microscopes' to understand how reactions occur at a molecular level, from simple reactions in solution to more complex biomolecular processes. Her team develops predictive models and computational tools to gain fundamental understanding of such processes and aid the optimisation and discovery of novel molecules to tackle industrial and societal challenges.
Biography
Professor Fernanda Duarte is Associate Professor in Computational Organic Chemistry at the University of Oxford and a Fellow of Hertford College. She completed her undergraduate and PhD studies at Pontificia Universidad Católica de Chile (PUC) in 2012. This was followed by a postdoctoral position at the Department of Cell and Molecular Biology at Uppsala University, where she pursued training in biomolecular modelling. Supported by a Newton Fellowship, she moved to the University of Oxford in 2015 working in the area of computational organic chemistry. Following a brief stint as a Chancellor’s Fellow at the School of Chemistry in Edinburgh she returned to Oxford in October 2018 as Associate Professor of Computational Organic Chemistry. During her career, Professor Duarte has received several awards, including the L'Oreal-UNESCO Women in Science award (2009), Pre-doctoral Fulbright scholarship (2010), Marie Curie Career Grant (2015), the Newton Fellowship (2015), and MGMS Frank Blaney Award from the Molecular Graphics and Modelling Society (2020). At Oxford, she leads a multidisciplinary research team working at the interface of organic chemistry, catalysis, and computational chemistry, establishing collaborations within academia and industry. Her team’s research interests centre on the prediction of chemical reactivity in the condensed phase, combining classical, quantum and machine-learning methods. Aside from research and teaching, Professor Duarte has taken an active role promoting diversity in STEM, more recently acting as the academic champion of the Women in Chemistry Society at Oxford and contributing to the LatinXChem initiative.
I did not consider it [chemistry] until very late, when I realised that it combined sciences and maths, my favourite subjects in school.
Professor Fernanda Duarte
Q&A with Professor Fernanda Duarte
How did you first become interested in chemistry?
Chemistry for me is an acquired taste. I did not consider it until very late, when I realised that it combined sciences and maths, my favourite subjects in school. I am happy that this rather serendipitous choice was the one that I took, as I don’t see myself doing anything else. It makes me very happy and keeps me challenged.
What motivates you?
The joy of understanding how chemistry works at the molecular level. I am also motivated by working with colleagues and students from whom I am continuously learning.
Can you tell us about a scientific development on the horizon that you are excited about?
Chemistry is a highly complex science. I am excited to see how insights from the fields of chemistry, data sciences, and automation are coming together to tackle pressing challenges by transforming the way new drugs and materials are obtained.
What has been a highlight for you (either personally or in your career)?
Seeing members of my team grow both personally and as independent scientists
What has been a challenge for you (either personally or in your career)?
Personally, learning English. I picked it up very late and failed my first university exam on the topic. In my career: making sure I mentor and support the researchers I work with.