Post-doctoral Fellow in Multi-Modal Imaging of Gynaecological Oncology
Work type: Full-time
Department: Department of Diagnostic Radiology, School of Clinical Medicine (20500)
Categories: Academic-related Staff
Applications are invited for appointment as Post-doctoral Fellow in Multi-modal imaging of gynaecological oncology in the Department of Diagnostic Radiology, School of Clinical Medicine (Ref.: 512332), to commence as soon as possible for two years, with the possibility of renewal subject to satisfactory performance and funding availability.
The Department of Diagnostic Radiology consists of a team of enthusiastic scientists and clinicians and is looking for a prospective team member to work on image processing and machine learning methods to assess disease presence, progression, and treatment response in clinical applications. The Department is equipped with clinical PET/CT and MRI machines as well as a dedicated GPU server for machine learning and deep learning applications and is pursuing important research questions in oncological imaging.
Applicants should possess a Ph.D. degree in Biomedical/Electrical Engineering, Computer Science, Biomedical Sciences, or a related field with an emphasis on quantitative analysis. They should have an excellent command of written and spoken English; excellent communications skills; demonstrated project management experience; and the ability to work independently, and collaborate and work in a highly multidisciplinary setting. They should also be attentive to detail; self-motivated; and willing to learn new skills and to think ‘outside the box’. Those with experience in image processing techniques in MATLAB and/or Python, data science, machine/deep learning, radiomics, segmentation and image registration are strongly encouraged to apply.
The appointee will design and develop specialised software, systems and tools; manage projects involving local and international collaborators; contribute technical expertise; prepare conference presentations, scientific papers and grant applications; collaborate with radiologists, physicians, biomedical scientists and engineers to generate new project ideas; and perform other duties as assigned. Enquiries about the post can be sent to Dr. Elaine Lee at firstname.lastname@example.org. Applicants who have responded to the previous advertisement (Ref.: 511301) need not re-apply.
A highly competitive salary commensurate with qualifications and experience will be offered, in addition to annual leave and medical benefits.
The University only accepts online application for the above post. Applicants should apply online and upload an up-to-date C.V. Review of applications will start as soon as possible and continue until May 31, 2022, or until the post is filled, whichever is earlier.