We are seeking an enthusiastic, ambitious and creative postdoc to join the Secrier lab (secrierlab.github.io/) at the UCL Genetics Institute on a UKRI-funded post, to lead the development of AI methodology for the detection of tumour dormancy and similar cellular states in digital pathology images of cancer tissue.
The post holder will be expected to develop various deep learning, machine learning, graph-based and data integration approaches on multi-omics and histopathology image datasets to uncover the spatial context of tumour dormancy and relate it to treatment outcome. Rich genomics, spatial transcriptomics and imaging datasets are available in oesophageal cancer from collaborators at the Universities of Cambridge and Southampton for this purpose. The post holder will also be expected to collaborate with our wet lab partners for the purpose of validation of the findings.
Funding for this post is available for 3 years subject to satisfactory performance.
Applicants must have a PhD in a relevant subject area, e.g. computer science, physics, bioinformatics, computational biology, statistics, mathematics or similar subject; extensive programming expertise and previous experience with machine learning or deep learning methods. Previous experience with NGS data and/or cancer is welcome but not mandatory.
For a full job description and to apply online for this vacancy please click here:
Informal enquiries should be directed to Maria Secrier on email@example.com
Closing date for applications: 27th December 2020