Research Assistant - £26,715 - £30,942
Research Associate* - £32,816 - £40,322
We are currently seeking a talented and motivated postdoctoral statistician to work on a joint project between the Cardiovascular Epidemiology Unit (Department of Public Health & Primary Care, University of Cambridge) and the MRC Biostatistics Unit. The post-holder will apply and develop cutting-edge Bayesian statistical methods for disentangling ("fine-mapping") the plethora of genetic association signals for blood-based biomarkers, such as proteins and metabolites, and diseases (eg, heart attack, stroke). Results from these methods will help to identify novel causes of cardiovascular diseases and potential targets for drug development.
The position is underpinned by a Cardiovascular Data Science Award funded jointly by the Alan Turing Institute (www.turing.ac.uk) and British Heart Foundation (www.bhf.org.uk). This award aims to foster collaboration between cardiovascular researchers and data scientists to generate novel data science solutions to key problems in cardiovascular science. This project aims to develop a new class of scalable statistical tools for fine-mapping multi-trait genetic association data. This will facilitate the identification of "shared" and "distinct" causal variants across multiple layers of phenotypic information (e.g., gene expression, cellular traits, proteins, metabolites, lipids and lipoproteins, known risk factors, disease outcomes). Given the focus on cardiovascular science, the initial test examples will be drawn from the ~200 known genetic association signals for heart disease or stroke. Data for testing and employing these new methods will be derived from the rich resources at the Cardiovascular Epidemiology Unit (https://www.phpc.cam.ac.uk/ceu/), including the INTERVAL study, a 50,000-person bioresource with imputed genome-wide array data on all participants, >100 haematological traits, >4,000 plasma proteins, ~>1,000 metabolites, >500 lipids and lipoproteins in subsets of participants. These data have recently been harnessed to discover ~2000 genetic signals for protein levels (Sun et al., Nature, 2018) and ~6000 genetic signals for blood cell traits (Astle et al., Cell, 2016).
A PhD in Statistics, Biostatistics or Computer Science (or a closely aligned discipline), or an equivalent level of professional qualifications and experience is essential. Applicants should also have a strong background in statistical modelling and computational statistics and able to implement algorithms in a low-level language (C, C++). Knowledge of approximate methods for Bayesian inference of large data sets such as Variational Bayes is also desirable. In addition to these skills, the post-holder should also be able to work independently judging priorities and have excellent organisational and communication skills.
*Appointment at research associate is dependent on having a PhD (or equivalent experience is recognised), including those who have submitted but not yet received their PhD. Where a PhD has yet to be awarded or submitted appointment will initially be made at research assistant and amended to research associate when the PhD is awarded awarded (PhD needs to be awarded within 6 months of the start date). If an individual has not submitted a PhD or is not working towards one they could be appointed as a Research Assistant if they have either a degree or Masters in a relevant area or equivalent experience.
This post is full-time and the funds for this post are available for 1 year from commencement in post.
The post-holder will work under the supervision of Dr Adam Butterworth (Department of Public Health & Primary Care, University of Cambridge) and Dr Leonardo Bottolo (MRC Biostatistics Unit and The Alan Turing Institute, London).
The post-holder will therefore be expected to spend time at both the Department of Public Health & Primary Care, located in Strangeways Research Laboratory (CB1 8RN, approx. 2 miles south of city centre), and the MRC Biostatistics Unit, located on the Cambridge Biomedical Campus and a 5 minute walk from Strangeways.
For an informal discussion about this post, please contact Dr Adam Butterworth (firstname.lastname@example.org) or Dr Leonardo Bottolo (email@example.com).
Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.
Closing Date: 24th August 2020
(Remote) Interview Date: Week commencing 7th September 2020
Please ensure that you upload a covering letter and CV in the Upload section of the online application. The covering letter should outline how you match the criteria for the post and why you are applying for this role. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application.
Please include details of your referees, including email address and phone number, one of which should be your most recent line manager.
Please quote reference RH23462 on your application and in any correspondence about this vacancy.
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