Research Associate* in Trustworthy MRI Reconstruction with Uncertainty Modelling
We welcome applications from candidates seeking appointment at the Research Assistant level.
Location: White City and South Kensington Campuses, Hybrid
About the role
We are looking for an enthusiastic research associate (post-doctoral) / research assistant (pre-doctoral) to make a leading contribution to a project on TrustMRI: Trustworthy and Robust Magnetic Resonance Image Reconstruction with Uncertainty Modelling and Deep Learning.
The objective of the post is to enable the advancement towards trustworthy and robust AI-based MRI reconstruction, through equipping them with the ability to model uncertainty and handle cases outside distribution. MRI is the leading diagnostic modality for a wide range of exams, but the physics of its data acquisition process makes it inherently slow. Recently, AI techniques have opened the possibility to accelerate this considerably, however, the lack of consideration of their trustworthiness and failure management limits their translational potential in clinical practice. The project will aim to develop advanced probabilistic deep learning methods that can reliably quantify and evaluate uncertainty for AI-based MRI reconstruction, as well as leveraging that for robust and adaptive deployment. The project will involve interdisciplinary research and close collaborations with academic and industrial partners.
Candidates with expertise in deep generative models, probabilistic modelling, active learning and computer vision/medical imaging are preferred. The successful candidate will be hosted by Department of Electrical and Electronic Engineering and the College’s new I-X initiative ( https://ix.imperial.ac.uk/ ), under the joint supervision of Dr Chen Qin ( https://cq615.github.io/ ), and Dr Yingzhen Li ( http://yingzhenli.net/home/en/ ), and work with a team of researchers and PhD students at Biomedical Image Analysis Group ( https://biomedia.doc.ic.ac.uk/ ).
What you would be doing
Key responsibilities include:
To take initiatives in the planning of research
To conduct original research with appropriate supervision
To write scientific papers and submit publications to high-quality conferences and journals
To present the research at leading international conferences
To open-source experimental software prototypes
To assist in the supervision of undergraduate and postgraduate research students as required
What we are looking for
To apply for this position, you must have a strong background in a subject relevant to computer science, mathematics, or a closely related discipline, and have experience, including a proven publication track-record, in one or more of the following areas: Probabilistic/Bayesian deep learning, uncertainty modelling, machine learning, computer vision and/or medical imaging.
You should also have:
Excellent communication and academic writing skills, demonstrated through a publication track record and/or presentations at scientific events
The ability to organise and prioritise your own work with minimal supervision
Strong analytical, problem-solving, organisational, and interpersonal skills
At Research Associate level* you must have been awarded a PhD (or equivalent) in a subject relevant to the post.
At Research Assistant level you will need to have a good (1st or 2:1) master and undergraduate degree in a relevant discipline.
What we can offer you
The opportunity to continue your career at a world-leading institution and be part of our mission to continue science for humanity.
Grow your career: gain access to Imperial’s sector-leading dedicated career support for researchers as well as opportunities for promotion and progression.
Sector-leading salary and remuneration package (including 39 days off a year and generous pension schemes).
Be part of a diverse, inclusive and collaborative work culture with various staff networks and resources to support your personal and professional wellbeing .
Further information
Candidates should attach the below documents in the online application:
A full CV, with a list of all publications
A 2-page research statement and proposal indicating what you see are interesting research issues relating to the above post and why your expertise is relevant.
Any element relating your experience / passion for software engineering (blog, open-source projects, GitHub repositories, and others) will be carefully inspected.
Should you require any further details on the role please contact: Dr Chen Qin – c.qin15@imperial.ac.uk .
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.
*Candidates who have not yet been officially awarded their PhD, or who hold a Bachelor’s or Master’s degree, will be appointed as Research Assistant with a salary range from £43,863 to £47,223. £49,017 to £57,472 per annum