PhD Studentship: Uncovering the (epi)Genomic regulation of cancer forming processes using integrative computational genomics and deep learning approaches (Application deadline: November 15th 2019)
This is a MRC funded studentship. UK residents only (EU residents that satisfy UKRI requirements can apply).
Project: Uncovering the (epi)Genomic regulation of cancer forming processes using integrative computational genomics and deep learning approaches
Mutations in oncogenes and tumour suppressor genes, copy number changes and other genetic aberrations, together with anomalous epigenomic modifications all conspire to alter gene expression programmes, perturb normal cellular processes and promote tumour formation. Perturbation of signaling pathways and networks, transcription factor binding patterns, reconfiguration of the three dimensional chromatin architecture, and changes in regulatory element activity and interactions enable tumour formation and cancer progression. Understanding these processes will enable development of therapies as well as development of cancer early detection applications. This project will use integrative computational approaches and large biomedical data-sets to develop and apply computational biology and machine learning (including novel deep learning solutions) methods to understand the complex systems involved in cancer formation and progression.
This project will bring together big data analytical, modelling, data-mining and visualisation approaches. Novel integrative methods will be developed and applied to multi-omic cancer datasets. Unique data integration approaches will be applied including modelling biological systems as knowledge graphs. Cutting edge computational biology and genomics approaches will be combined with deep learning methods (Convolutional neural networks (CNNs), generative methods such as variational autoencoders (VAEs) and generative adversarial networks (GANs) together with other machine learning methods.
A masters degree in a quantitative field (data science, machine learning, deep learning, computational biology, mathematics, statistics or engineering) is required.
Candidates with Biomedical or Medical degrees with exceptional (R and/or Python) programming and analytical skills with a good understanding of cancer biology, immunology or metabolism are also welcome to apply.
How to apply: Applications will need to be made through the University Application Portal and will entail an application fee of £65. Please visit: applications for further information about the programme and to access the Applicant Portal. Please note that the course code for PhD applications to the MRC Cancer Unit is MDCU22. Whilst making your online application please make it clear which project area(s) and principal investigator(s) you are interested in working with. Your online application needs to include:
• A CV, including full details of all University course grades to date. • Contact details for two academic or professional referees.
• A personal statement outlining your interest in a specific project area, what you hope to achieve from a PhD, and your research experience to date.
The above information must be provided under relevant sections on the application portal.
READ before applying
Qualifications & Funding requirements:
We're a Computational Biology & Data Science lab. If you want to do experimental biology we're not the right lab for you. The ideal Masters or Ph.D. student should have a degree in a quantitative field (Mathematics, Statistics, Computer Science, Data Science, Machine Learning, Computational Biology, Physics or Engineering). You should also meet University of Cambridge admission requirements and degree pre-requisites.
We advertise Ph.D. studentships from time to time. Depending on the studentship type there may be various requirements and restrictions. If you're applying outside of advertised studentships, funding sources need to be found. Keep a lookout for funding sources and deadlines.
Undergraduate interns and summer student should have good programming skills in python or R and, If you are from a Biomedical or Medical background, exceptional programming skills are essential.
We advertise Post-doctoral positions from time to time. Email me if you have your own fellowship or wish to apply for external fellowships to join the lab.
Email me if you meet any of the above requirements and wish to join the lab.