We are seeking a Post-Doctoral Researcher to join the Dingwall Lab on a six-month position with a funding end date of 31 March 2021. The position is fully lab based; you will assist in the collection of kinetic data from homogeneously catalysed reactions which will be used by our collaborators in the School of Computer Science (Mai lab) to predict reaction outcomes with machine learning techniques. The position is funded 85% FTE and so the candidate will be expected to work no more than four days a week.
Predicting the performance of a reaction is a challenging task. The rare reports that do so use machine learning algorithms that are fed a huge volume of single timepoint yield data normally generated via high throughput experimentation. Using single timepoint yields to represent reaction outcomes is a major shortcoming of existing approaches and we propose that kinetic data will outperform single timepoint yield data in predicting reaction performance. The project has been funded as part of the Artificial Intelligence and Augmented Intelligence for Automated Investigations for Scientific Discovery (AI3SD) Network+ and candidates will also be given the opportunity to co-author a Wiley book chapter on machine learning in Chemistry.
The successful candidate must have:
Have a degree in Chemistry or a related discipline (minimum standard 2:1)
Have a PhD in Chemistry or a related discipline
At least three years research experience involving physical organic chemistry, synthetic organic chemistry, or related disciplines.
Proven experience of applying core analytical techniques (NMR, GC, HPLC)
For full job details and criteria please see the Candidate Information link on our website by clicking ‘apply’. You must clearly demonstrate how you meet the criteria when you submit your application. For further information please contact Resourcing Team, Queen's University Belfast, BT7 1NN. Telephone (028) 9097 3044 or email email@example.com.
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