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Research Associate
3 months ago
Supported by several Horizon Europe, European Research Council, UK Research and Innovation, British Heart Foundation, and industry funded projects, my Smart Imaging Lab ( is seeking a highly motivated, post-doctoral fellow for advanced quantitative MRI and PET imaging. Ongoing projects include cardiovascular MRI for atrial fibrillation, congenital heart disease, CT and chest X-ray for lung fibrosis, multimodal imaging for cancer, and deep learning algorithms development including medical image/data analysis, segmentation, classification and reconstruction.
I am now seeking three postdoctoral Research Associates to join my group and work on this project funded by the UKRI. The post aims to improve the speed and scalability of various MRI and PET techniques, adding the ability to predict outcomes early in the clinical course, and empowering citizens and patients to participate in their diagnosis, care, and preparedness will increase the capacity of health systems and accelerate the pace of research and innovation.
The main contribution of the group led by Dr Guang Yang to this UKRI funded project focuses on developing advanced approaches such as physics driven artificial intelligence for fast MRI and PET imaging. In this project, the aim is to elevate the novel imaging technologies in a wide range of clinical studies.
There will be opportunities to collaborate with other researchers and PhD students in the group and wide national and international collaborations, which include top-tier UK/EU research institutes and high-tech companies, including Technical University of Munich, University of Bern, Cambridge University, Maastricht University, European Respiratory Society, European Lung Foundation, Siemens and others.
Applicants must demonstrate as part of their application, how they meet the essential criteria required of the post. In particular, Research Associate applicants must hold a PhD in a relevant discipline and all applicants should have equivalent laboratory experience. In addition, applicants 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: diffusion models,
generative adversarial models, deep learning and its applications to medical image analysis, imaging biomarkers extraction, diagnosis and prognosis. The successful candidate will have demonstrated a practical knowledge of MRI pulse sequence programming, and a comprehensive understanding of MRI and PET reconstruction, and/or translational science, as evidenced by quality in peer-reviewed publications. The applicants for Research Associate should have or be close to completion of a PhD degree (or equivalent) in an area pertinent to the subject area, ., MR Physics, Computing or Engineering. Experience in Siemens pulse sequence programming and deep learning knowledge is a plus. The successful candidate must have excellent verbal and written communication skills, enjoy working collaboratively and be able to organise his/her 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.
The opportunity to continue your career at a world-leading institution sector-leading salary and remuneration package (including 38 days off a year)