Prof Crispin Miller
The combined analysis of microscopy images with molecular measurements, such as patterns of gene expression and mutation profiles, are making it possible to generate deep mechanistic insights into the processes that underpin tumour development and disease progression. An increasingly important aspect of cancer research is the use of machine learning and data science to analyse the rich multi-modal datasets arising from these studies.
About us
The CRUK Beatson Institute is one of Europe's leading cancer research centres, situated in Glasgow and hosting approximately 250 talented researchers at all research stages. We are renowned for our world-class in vivo modelling of tumour growth and metastasis and have an excellent reputation for cutting-edge fundamental and translational research in our three key strategic areas: biology of early disease; energetic stress / cancer metabolism; and microenvironment / metastasis. As well as generous core funding from Cancer Research UK, the Institute receives an additional third of its total income from external grants and industry collaborations. We pride ourselves on our highly collaborative research environment fostered by our outstanding state of the art high performance computing, advanced imaging, proteomic, metabolomic and spatial profiling technologies and expertise.
Project outline
We are seeking a bioinformatics software engineer to join our expanding data science team to develop computational workflows, Machine Learning approaches and analysis pipelines to support the interrogation of multiomics datasets. These will include single cell analyses spatial transcriptomics data, comparative genomics, and multiplex imaging datasets arising from in vivo and in vitro models, generated across cell lines, organoids, mouse models, and human tumours.
A PhD in computational biology or related discipline is a pre-requisite. The successful applicant will have significant coding and scripting experience in languages such as C/C++, Python, and R, and will be familiar working with large complex datasets. Experience with deep learning algorithms would convey a significant advantage, but is not a pre-requisite. Excellent statistical acumen, and the ability to communicate across disciplines is essential.
The post will appeal to applicants with a strong desire to see computational techniques applied to real-world data in order to improve our understanding of cancer, and ultimately, to improve patient outcome. The successful applicant will join a highly collaborative, inclusive and multidisciplinary team that encompasses computer science, clinical- and basic-biology, statistics and mathematics.
For informal enquiries please email Prof. Crispin Miller at:
Crispin.Miller@glasgow.ac.uk.
Closing Date: 01/07/2022