Prof Crispin Miller, Prof Martin Bushell
Targeting regulatory sequences in tumours
As a world-leading cancer research centre, the CRUK Beatson Institute supports cutting edge work into the molecular mechanisms of cancer development. We provide an outstanding research environment, underpinned by state-of-the-art core services and advanced technologies with special emphasis on imaging and in vivo models.
We are looking for students with a very good degree in a Life Sciences subject and an aptitude for experimental work, who are also highly committed to pursuing a PhD and a career in cancer research. The Beatson has an excellent reputation and success record in training its graduate students. Students, whilst being trained at the Institute working within our research groups, will matriculate with the University of Glasgow.
Our PhD studentships are for a maximum of 4 years, and currently provide students with an annual stipend of £19,000 and matriculation fees for home, EU or overseas students.
Protein expression is tightly regulated by multiple interlocking systems that encompass all stages of transcription, mRNA processing and translation.
The Computational Biology Group (Miller) is interested in how sequence patterns, including DNA and RNA modifications encode the regulatory signals that interact with the mRNA processing and translational machinery. A PhD studentship is available to investigate the regulatory role of these loci and to explore their potential as novel tumour suppressors and oncogenes. The post will entail working with multiomics data derived from in vitro and in vivo studies and integrating these with tumour sequencing data. These will be investigated at the bench in collaboration with the RNA and Translational Control in Cancer lab (Bushell) to develop a more detailed mechanistic understanding of their role both in tumour and normal cells, and to ask how this knowledge might be used to advance patient care.
Applicants from both computing and biological backgrounds interested in integrating molecular- and computational approaches are encouraged to apply. The project offers an excellent cross-disciplinary training opportunity rooted in existing collaborations between our labs, and the opportunity to work with datasets arising from multiple state of the art technologies including DNA- and RNA-sequencing, single cell genomics, proteomics, advanced imaging, and spatial transcriptomics.