The MRC Toxicology Unit is an internationally renowned institution focussed on the delivery of field-changing mechanistic insights into toxicology and disease. The Unit is equipped with state-of-the-art facilities and offers excellent opportunities for postdoctoral development. The Unit is currently based in Leicester and will relocate to Cambridge in 2020.
We are looking to appoint a postdoctoral computational biologist/biostatistician to join the laboratory of Dr. John Le Quesne as part of an exciting new research alliance between UK-based RNA biologists and CRUK's Therapeutic Discovery laboratories. The aim of this alliance is to develop novel cancer therapies against several novel targets within the translational control apparatus.
The Le Quesne laboratory uses quantitative histopathological and molecular methods to investigate the expression of drug targets and their relationships with tumour biology and genomics in large collections of primary human tumour tissue. We are establishing very large collections of primary human tissue from thoracic malignancies, and have access to collections of several other common malignancies via the research alliance. We have an established pipeline for the generation of quantitative data, and for its incorporation into our tumour databases. Quantitative assays for target protein antigens, mRNAs, and markers of tumour phenotype are established in the laboratory and fully supported by our core histopathology facility.
The successful applicant will normalise, model and interpret data from in situ and genomic assays in order to understand how translational dysregulation is related to patient outcomes and to measured tumour phenotypes & genotypes. They will help to develop quantitative image analysis algorithms using purpose-built software. Data modelling methods to be implemented include longitudinal survival analyses and regression modelling. They will have excellent skills in handling large datasets. Direct experience with cancer patient data and/tissue microarray data/nucleic acid microarray statistical methods will be advantageous.
Applicants must have (or be in the final stages of receiving) a higher degree (PhD) in bioinformatics/biostatistics OR a PhD in cancer biology/biochemistry with a substantial bioinformatics component. A proven ability with high-level biostatistical software packages together with experience and understanding of univariate and multivariate longitudinal survival modelling methods; regression modelling and the ability to develop and apply novel statistical models for biological inference is essential. Direct experience with cancer patient data and/tissue microarray data/nucleic acid microarray statistical methods will be advantageous. Evidence of publishing high quality research in a peer reviewed journal; the ability to work independently and as part of a team, together with excellent communication and problem solving skills are required.
Further information on the Toxicology Unit can be found at www.mrc-tox.cam.ac.uk
This post is for three years, funded by Celgene.
Fixed-term: The funds for this post are available for 3 years in the first instance.
Once an offer of employment has been accepted, the successful candidate will be required to undergo a basic disclosure (criminal records check) check and a health assessment.
To apply online for this vacancy, please click on the 'Apply' button below. This will route you to the University's Web Recruitment System, where you will need to register an account (if you have not already) and log in before completing the online application form.
If you have any queries regarding the application process please contact Rebecca Heatherley on firstname.lastname@example.org
Please quote reference PU15035 on your application and in any correspondence about this vacancy.
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