Research Associate in Machine Learning for X-ray Spectroscopy

Key Skills

Deep Learning, Machine learning techniques, Neural Networks, Python Programming

Job Description

We are a world class research-intensive university. We deliver teaching and learning of the highest quality. We play a leading role in economic, social and cultural development of the North East of England. Attracting and retaining high-calibre people is fundamental to our continued success.

The Role

Does your expertise lie in data science techniques and/or theoretical spectroscopy. Do you have a passion to develop your knowledge to transform the analysis of X-ray spectroscopy using Deep Neural Networks. If so, we would love to hear from you.

We are seeking to recruit a part-time research associate to advance the development of deep neural networks for real-time spectroscopic analysis. Based in Chemistry at Newcastle University, as a Research Associate you will develop and use supervised machine learning/deep learning algorithms to transform the analysis of X-ray spectroscopy by developing and using easy-to-use, computationally inexpensive, and accessible tools for the fast and automated analysis of X-ray spectroscopy. This builds upon recent proof-of-concept work we have performed, e.g. https://aip.scitation.org/doi/abs/10.1063/5.0087255 and https://pubs.rsc.org/en/content/articlehtml/2021/cp/d0cp06244h.

You will have an undergraduate degree in a relevant science subject, preferably chemistry, physics or computer science; a PhD in computer science, theoretical or computational chemistry or a related discipline (candidates who have submitted their thesis will be considered). You will also have expertise in calculating spectroscopic observables or implementing deep learning algorithms as well as experience with a computer programming language, preferably Python.

This is a part-time position.

The duration of the appointment will be initially 12 months. The start date is flexible but ideally will be before September 2024.

To apply, please complete the online application, and provide evidence of how you meet the essential criteria required for the role outlined in ‘The Person' by uploading a letter of application along with your Curriculum Vitae (CV).

Informal approaches can be made to Prof. Thomas Penfold at tom.penfold@ncl.ac.uk.

Information about the group can be found at: http://www.penfoldgroup.co.uk.

For further details about Newcastle University please visit our information page at: http://www.ncl.ac.uk/about.

For more information about the School of Natural and Environmental Sciences please click here.