Research Assistant / Associate for National Heart and Lung

Imperial College London National Heart and Lung Institute

United Kingdom

Job summary

We are seeking either a Research Assistant or Research Associate to work in this project. The post is funded by the EU H2020 CHAIMELEON project and aims to demonstrate for first time that AI can be used to enhance reproducibility of radiomics features and parameters extracted from cross-vendor and cross-institution CT-MR-PET/MR imaging data. Increasing favourable outcomes suggests that health imaging-based AI approaches can become useful...

Job listing information

  • Reference MED02046
  • Date posted 2 October 2020
  • Closing date 1 November 2020

Key information about the role

  • Location Royal Brompton Campus (map)
  • Position type Full time, fixed term
  • Salary £35,477 – £45,615 plus benefits
  • Department National Heart & Lung Institute
  • Category Researcher / Non Clinical Researcher

Job description

Job summary

We are seeking either a Research Assistant or Research Associate to work in this project. The post is funded by the EU H2020 CHAIMELEON project and aims to demonstrate for first time that AI can be used to enhance reproducibility of radiomics features and parameters extracted from cross-vendor and cross-institution CT-MR-PET/MR imaging data.

Increasing favourable outcomes suggests that health imaging-based AI approaches can become useful clinical tools in areas such as non-invasive tumour characterisation, prediction of certain tumour features, staging of tumour spread, stratification of patients, selection of most appropriate therapies and clinical prognosis.

Duties and responsibilities

The main contribution of the group led by Dr Guang Yang to CHAIMELEON project focuses on the investigation and development of novel data quality enhancement and harmonisation,  and federated machine learning algorithms for cross-vendor and cross-institution AI powered data repository construction, including the investigation of new strategies in medical imaging acquisition, reconstruction, as well as novel mechanisms to generate adversarial examples and mitigate their effects. The work also includes the analysis of scenarios where data privacy can be enhanced for large multimodal clinical data repository.

There will be opportunities to collaborate with other researchers and PhD students in the CHAIMELEON consortium, which includes 18 top-tier UK/EU research institutes and high-tech companies.

Essential requirements

Applicants must demonstrate as part of their application, how they meet the essential criteria required for the post. To be appointed as a Research Assistant you should have or be close to completion of a PhD degree (or equivalent) in an area pertinent to the subject area, i.e., Computing or Engineering, for the Research Associate position, or a good first degree in related area for the Research Assistant position. You must have excellent verbal and written communication skills, enjoy working in collaboratively and be able to organise your own work with minimal supervision and prioritise work to meet deadlines. Preference will be given to applicants with a proven research record and publications in the relevant areas, including in prestigious machine learning, computer vision and medical image analysis journals and conferences.

In particular, Research Associate applicants must hold a PhD in a relevant discipline and all applicants should have equivalent laboratory experience. In addition, you will need to have a strong machine learning background with proven knowledge and track record in one or more of the following research areas and techniques: generative adversarial models, federated or distributed machine learning, deep learning and its applications to medical image reconstruction, denoising and data harmonisation.

Further information

The post is full time and fixed term for up to 36 months.

Candidates who have not yet been officially awarded their PhD will be appointed as a Research Assistant within the salary range £35,477 - £38,566 per annum.

Should you require any further details on the role please contact: Dr Guang Yang – g.yang@imperial.ac.uk.

For technical issues when applying online please email recruitment@imperial.ac.uk.

Committed to equality and valuing diversity, 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.

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


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