PhD Studentship - Cancer Bioinformatics: Connecting Cell-Cell Signalling in the TME | UCL Cancer Institute - UCL

This 4-year Cancer Research UK project will fund an exceptional UK/EU bioinformatic PhD student to study cell-cell communication in cancer using single-cell data.

Primary supervisor: Dr Chris Tape
Secondary supervisor: Prof Javier Herrero
Earliest start date: September 2019

Closing date: Monday 1 July 2019 (17:00 BST)

Tumours comprise mutated cancer cells, stromal fibroblasts, and multiple immune cells. While each of these cell-types can contribute towards cancer, how they interact to support tumours is poorly understood. To fully comprehend multicellular diseases like cancer, we must study how different cell-types communicate.

The Cell Communication Lab at UCL Cancer Institute investigates how cells interact. Specifically, we use custom single-cell technologies (including CyTOF and single-cell RNA-seq) to study how mutations in cancer cells signal through all the major cell-types in colorectal cancer (CRC). A major bottleneck of this approach has been the limited computational tools available to analyse such unique data.

This 4-year Cancer Research UK project will fund an exceptional UK/EU bioinformatic PhD student to study cell-cell communication in cancer using single-cell data. The PhD student will start by building computational tools to investigate intracellular signalling. The student will then use cutting-edge proteogenomic methods (integrating single-cell protein and RNA data) to understand how cell-specific ligand and receptor expression connects different cells. The student will then use this data to build detailed intra- and inter-cellular communication networks of tumours. The project will use both statistical and machine learning technologies – spanning both proteomics and genomics. By studying novel computational methods to understand cell-cell communication, this project has the potential to revolutionise our understanding of tumour biology.

The PhD student will be supervised by Dr Chris Tape (Cell Communication Lab, UCL Cancer Institute) and Prof Javier Herrero (Bill Lyons Informatics Centre, UCL Cancer Institute). Earliest start-date: Sept. 2019.

More detailed information about the research project is available on request from c.tape@ucl.ac.uk (Twitter: @christophertape).

Duties and responsibilities

Research

To apply highly specialist scientific skills and expertise to lead in the delivery of high quality research and the preparation of high-impact research publications.
To keep abreast of current developments in this research area.
To report research progress to the supervisory team, the Cancer Institute, and at scientific conferences and meetings.
To work with other Scientists within the team as necessary.
To work safely by adhering to all University policies and practices, including preparing and following laboratory risk assessments, and complying with Health and Safety policies, ethical approval processes and Human Tissue Act guidelines.

Analytical and Judgement Skills

To demonstrate a high-level of technical and analytical skill to resolve highly complex scenarios, requiring analysis, interpretation and expert judgement to find the most appropriate solutions.
To identify, interpret and integrate information from a wide variety of sources, and critically evaluate the quality and assumptions of these data.
Show initiative and the ability to make decisions in areas where no previous work has been undertaken.
Show awareness of your own developmental needs and undertake appropriate training where appropriate.
To comply with professional codes of conduct.

Person specification

Essential

Minimum upper second class Honours Degree in an associated discipline, or an overseas qualification of an equivalent standard.
Proficiency in large-scale biological data analysis using R, Python, and/or other appropriate programming languages.
Evidence of motivation for and understanding cell-signalling in cancer.
Ability to develop understanding of complex problems and apply in-depth knowledge to address them.
Potential to develop expertise in new areas of the subject.
Potential for innovation and initiative, and evidence of an ability to work independently.
Effective communication skills in both written and spoken English.

Desirable

Experience with high performance computing (HPC) platforms.
Experience with machine learning programming environments (e.g. TensorFlow).
Experience with deep learning architectures (e.g. deep autoencoders, restricted Boltzmann machines, deep belief networks, and convolutional neural networks). Experience with mutual information analysis.

Students will need to qualify as UK/EU fee payers and meet UCL general admissions criteria.

Research environment

The UCL Cancer Institute is a state-of-the-art institute to consolidate cancer research at UCL and promote links with our partner teaching hospitals, in order to support excellence in basic and translational studies. The Institute draws together talented scientists who are working together to translate research discoveries into developing kinder, more effective therapies for cancer patients. It is a Cancer Research UK and Experimental Cancer Medicine Centre, and contains approximately 580 staff, including 80 PhD and MD (Res) students and 30-40 MSc students. Core facilities within the Institute include: Genomics Facility (gene expression microarrays); Proteomics Facility; Imaging and Cell Sorting (confocal, time-lapsed microscopy, MoFlo FACS); Pathology Suite (laser capture microdissection, tissue arrays); Experimental Imaging (with UCL Institute of Child Health); and Transgenesis.

Eligibility

Students will need to qualify as UK/EU fee payers and meet UCL general admissions criteria.

Application Procedure

To apply for this studentship, please submit only two documents:

1. Your full CV including a short summary (<500 words) detailing how your experience and ability matches the project and the person specification.

2. A single PDF file containing scans of two reference letters, one of which must be academic, and the award certificate and transcripts showing your unit/module marks for all of your degrees, undergraduate and postgraduate. If any of your original documents are not in English you must submit an official English translation with them.

These two documents should then be emailed to CI.Scholarships@ucl.ac.uk with the studentship code 'Tape02' and your surname both in the subject line of the email.

Complete applications must be received by Monday 1 July 2019 17:00 (BST). Incomplete applications will not be forwarded to the Shortlisting Panel. Queries about the application procedure or recruitment process should be directed to: shoukia.bhatti@ucl.ac.uk.