The Department of Chemical Engineering and Biotechnology is seeking a person interested in obtaining a PhD in the area of novel methods of chemical processes development based on machine learning and high throughput flow synthesis technology. The successful candidate will be supervised by Prof. Alexei Lapkin and take part in the "Synthesis of new active materials for flow batteries" project, which is part of the European Doctoral Network "PREDICTOR": High-throughput screening, synthesis and characterization of active materials for flow batteries.
Marie Sklodowska-Curie Doctoral Networks are joint research and training projects funded by the European Union. Funding is provided for doctoral candidates from both inside and outside Europe to carry out individual project work in a European country other than their own. The training network "PREDICTOR" is made up of 22 partners, coordinated by Fraunhofer ICT in Germany. The network will recruit a total of 17 doctoral candidates for project work lasting for 36 months.
PREDICTOR aims to establish a rapid, high-throughput method to identify and develop materials for electrochemical energy storage. It will enable the rapid identification, synthesis and characterization of materials within a coherent development chain, replacing conventional trial-and-error developments. To validate the PREDICTOR system, the case study will be active materials and electrolytes for redox-flow batteries. Within the project, three demonstrator battery cells (TRL3-4) will be assembled and tested with the newly developed materials.
As part of the project, the post holder might take on short secondments in PREDICTOR academic and industrial partners.
Minimum Requirements:
* Not having resided in the UK for more than 12 months in the three years immediately before the recruitment date, and not having carried out their main activity (work, studies, etc.) in the UK during this period.
* Having a master degree or equivalent diploma, and not having a doctoral degree.
* First degree in chemistry or chemical engineering.
* Interest in novel synthesis technologies, such as automated synthesis, flow chemistry and high-throughput synthesis.
* Experience with/(interest in) computation, coding (Python) and machine learning.
The salary and benefits will follow the principles of the Marie Curie Doctoral Network Scheme as underwritten by the UKRI. Living allowance, mobility allowance and, if appropriate, family allowance, will be paid in GBP at a fixed exchange rate of 1.148787.
Fixed-term: The funds for this post are available for 3 years.
Closing date for applications is 30th November 2024.
Please quote reference NQ43593 on your application and in any correspondence about this vacancy.
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.
The University has a responsibility to ensure that all employees are eligible to live and work in the UK.
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