Dr Piers Townsend

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About me

Fundamentally, our ever-evolving world is continuously faced with new challenges to solve. I believe that interdisciplinarity and collaboration are vital in solving the next generation of scientific problems, and it is with this ethos that I pursue my work.

Since the start of my research career, my work has largely been focused on the use of computational chemistry in predictive toxicology. As a result of my PhD work, numerous first-author publications in internationally recognised, peer-reviewed journals were produced. I thoroughly enjoy the experience of working with other people, and the process of interdisciplinary collaboration. From this enjoyment, I have contributed to a number of publications across a range of disciplines including toxicology, molecular modelling, machine learning and environmental science. If you would like to collaborate, please do reach out; I would love to hear from you.

More broadly and moving forward, I have a deep interest in exploring how computational chemistry, machine learning, and their combined interplay can be used to solve problems in environmental science. 

In my spare time, I enjoy playing video games, spending time by the coast, looking after my greyhound, and reading a range of different genres.

Area of expertise

Broadly speaking, my research is focused on building predictive in silico models using tools from computational and theoretical chemistry. My research is multi-disciplinary in nature, and straddles the border of chemistry, physics and biology. Although my research interests are varied, I have an overarching interest in how computational chemistry, cheminformatics, and machine learning can be combined to solve problems in environmental chemistry. I have particular interest in aquatic environments, and how the aforementioned tools can be applied to solve the next generation of challenges facing both marine and freshwater environments.

Research Interests:

  • The Application and Development of QSAR Models for Environmental Toxicology
  • Chemical Reaction Modelling
  • Machine Learning 

Publications

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