Dear all,
We have a PhD position applying HPC to the analysis of large scale cancer datasets. The post will suit an applicant from a strong computational background who wishes to apply their knowledge to help develop a better understanding of the processes that control how tumours develop.
Details below:
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High Performance Computing applied to cancer research: Computational analysis of Noncoding RNA regulators of gene expression in individual tumour cells
RNABiology/Computational Biology
The goal of this project is to use computational tools to ask how patterns in gene expression are disrupted in cancer. The project will suit a graduate student from a computational background with exceptional programming ability and strength in mathematics and statistics.
The main focus of our group is directed at understanding the role played by noncoding RNAs (ncRNAs) in modulating the behaviour of cancer cells. These are RNA molecules that are transcribed, but never translated into protein sequences. Advances in sequencing technology have revealed large numbers of novel ncRNA loci in the genome, to the point where they are now known to outnumber protein-coding genes. Whilst most are uncharacterised, recent work has shown an increasing number to be functional – and to act in a variety of regulatory roles within the cell. The successful applicant will join a highly interdisciplinary team comprising numerical- and biological-scientists who together exploit the power of new technologies such as single-cell RNA sequencing and protein mass spectrometry to investigate the fundamentals of gene expression in cancer. This project will involve applying machine learning and pattern recognition techniques to high volumes of RNA-sequencing data representing a combination of single cells, clinical samples, and experimental data generated using cell lines.
The scale of the data mean that novel algorithms will be required in order to achieve the volume of computation required, and this will involve programming on the latest architectures. The successful applicant will make extensive use of our on-site High Performance Computing (HPC) facility, purpose built for the analysis of cancer genomics data. Experience coding in C, C++ or Java are critical, and familiarity with aspects of graph theory, machine learning, and parallel programming will be advantageous. While an understanding of basic genomics and cancer biology would be useful, it is not a prerequisite; the project is open to an enthusiastic individual from a numerical discipline who wishes to use their skills to help develop a better understanding of the processes that control gene expression, and how they are perturbed in tumours.
Please visit our website to find out more: http://www.cruk.manchester.ac.uk/Education/PhD-Studentships/2015-Projects
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