Purpose of the Post
To undertake and disseminate internationally leading research into the development of a range of the next generation data driven models and applications to healthcare (Healthy Nation), energy (Resilient Nation), manufacturing and digital technologies (Resilient Nation, Productive Nation) as areas to drive economic growth in the context of the PREdictive Modelling with QuantIfication of UncERtainty for MultiphasE Systems (PREMIERE) project. The Research Associate will collaborate with and strengthen the multi-disciplinary team of researchers already in place working on closely related projects. Ultimately the post holder will contribute to the delivery of a next generation data driven models including reduced order models, data assimilation and machine learning.
The Research Associate will work at the Data Science Institute (DSI) and, within the DSI, the post holder will be member of the DataLearning working group.
Candidates who have not yet been officially awarded their PhD will be appointed as a Research Assistant £36,045- £39,183
Duties and responsibilities
Duties and responsibilities
You will be expected to:
- plan and carry out research in accordance with the project aims and under instruction from the project investigators
- To take initiatives in the planning of research
- To direct the work of small research teams
- To identify and develop suitable techniques, and apparatus, for the collection and analysis of data
- To conduct data analysis
- To ensure the validity and reliability of data always
- To maintain accurate and complete records of all findings
- To write reports for submission to research sponsors
- To present findings to colleagues and at conferences
- To submit publications to refereed journals
- To provide guidance to staff and students
Candidates who have not yet been officially awarded their PhD in Mathematics, Physics, Computing, Engineering or significant experience will be appointed as Research Assistant level
In addition, you must meet the following criteria:
- Experience of implementation of data assimilation techniques within complex multi-physics unstructured adaptive mesh models, and in particular fluid dynamics Experience of implementation of data assimilation techniques within complex multi-physics unstructured adaptive mesh models, and in particular fluid dynamics
- Experience of modern programming in languages including Fortran, C++ and Python
- Experience working within substantial scientific computational projects and large multi-disciplinary environments.
- Experience in running Computational Fluid Dynamic simulations
Where Imperial or funder conditions necessitate, you will be required to complete timesheets for your work on projects in a timely manner.
This is a full-time position, for up to 22 months
How to apply:
Via our website at https://www.imperial.ac.uk/jobs and search using vacancy reference number: ENG01559
For queries regarding the application process contact Fay Miller firstname.lastname@example.org
For technical issues when applying online, please contact: email@example.com
Closing date:11 March 2021
The College is a proud signatory to the San-Francisco Declaration on Research Assessment (DORA),which means that in hiring and promotion decisions, we evaluate applicants on the quality of their work, not the journal impact factor where it is published. For more information, see https ://www.imperial.ac.uk/research-and-innovation/about-imperial-research/research-evaluation/
The College believes that the use of animals in research is vital to improve human and animal health and welfare. Animals may only be used in research programmes where their use is shown to be necessary for developing new treatments and making medical advances. Imperial is committed to ensuring that, in cases where this research is deemed essential, all animals in the College’s care are treated with full respect, and that all staff involved with this work show due consideration at every level. http://www.imperial.ac.uk/research-and-innovation/about-imperial-research/research-integrity/animal-research/
Imperial College is committed to equality of opportunity, to eliminating discrimination and to creating an inclusive working environment. We are an Athena SWAN Silver award winner, a Stonewall Diversity Champion, a Disability Confident Employer and work in partnership with GIRES to promote respect for trans people.
Please note that job descriptions cannot be exhaustive and the post-holder may be required to undertake other duties, which are broadly in line with the above key responsibilities.
All Imperial employees are expected to follow the 7 principles of Imperial Expectations:
- Champion a positive approach to change and opportunity
- Communicate regularly and effectively within, and across, teams
- Consider the thoughts and expectations of others
- Deliver positive outcomes
- Encourage inclusive participation and eliminate discrimination
- Develop and grow skills and expertise
- Work in a planned and managed way
In addition to the above, employees are required to observe and comply with all College policies and regulations.
We are committed to equality of opportunity, to eliminating discrimination and to creating an inclusive working environment for all. We therefore encourage candidates to apply irrespective of age, disability, marriage or civil partnership status, pregnancy or maternity, race, religion and belief, gender identity, sex, or sexual orientation. We are an Athena SWAN Silver Award winner, a Disability Confident Leader and a Stonewall Diversity Champion.
For technical issues when applying online please email firstname.lastname@example.org .