Postdoctoral Research Fellow - Bioinformatics

The Institute of Cancer Research
Sutton
6 months ago
Applications closed

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Machine Learning (Algorithm Development)

Professor Johann de Bono’s translational research team is seeking a talented Post-doctoral Research Fellow. The programme focuses on integrating multi-omic and clinical data, including single cell and spatial data as well as hyperplex immunocytochemical data, to help develop novel therapeutic strategies against cancer.

For general information on Post Doc's at The ICR can be found here.

Key Requirements

The successful candidate will be highly motivated and possess robust bioinformatic, scientific, and analytical skills, with a proactive approach to learning and applying new techniques, including artificial intelligence. Primary responsibilities will involve working with integrated datasets including clinical trial datasets comprising next-generation sequencing data and other applications relevant to the analysis of DNA and RNA sequencing, as well as protein assays. Familiarity with cancer genomics is desirable.

The ICR has a workforceagreement stating that Postdoctoral Training Fellows can only be employed for up to 7 years as PDTF at the ICR, providing total postdoctoral experience (including previous employment at this level elsewhere) does not exceed 10 years

Department/Directorate Information:

Professor Johann de Bono is a world leader in anticancer drug development, biomarker studies, and prostate cancer care. His team conducts biomarker-driven clinical and translational research to accelerate the development of novel cancer therapies and improve understanding of cancer biology, drug sensitivity and resistance. His team has driven major advances in cancer care through early and late stage trials, and he has led pivotal phase III trials of several prostate cancer drugs including abiraterone, cabazitaxel, enzalutamide, lutetium PSMA and olaparib. His team consists of basic, translational and clinical scientists, and is embedded in a vibrant world-class research environment.

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