Research Associate (Fixed Term)
The MRC Biostatistics Unit is one of Europe's leading biostatistics research
institutions. Our focus is to deliver new analytical and computational
strategies based on sound statistical principles for the challenging tasks
facing biomedicine and public health. The Unit is situated on the Cambridge
Biomedical Campus, one of the world's most vibrant centres of biomedical
research, which includes the University of Cambridge's Clinical School, two
major hospitals, the MRC Laboratory of Molecular Biology, and the world
headquarters of Astra Zeneca.
An opportunity has arisen for a talented statistician within the Precision
Medicine and Inference for Complex Outcomes theme. The successful applicant
will have the opportunity to contribute to the Bringing Innovative Research
Methods to Clustering Analysis of Multimorbidity (BIRM-CAM) project between
the Universities of Cambridge and Birmingham, funded by the UK Medical
Research Council (MRC) and the National Institute for Health Research
(NIHR). The project is led by Profs. Sylvia Richardson (Cambridge) and Tom
Marshall (Birmingham). Within the MRC Biostatistics Unit, Drs. Jessica
Barrett, and Paul Kirk are also part of the BIRM-CAM team.
Multimorbidity is when people suffer from more than one long-term illness. It
is increasingly common as people live longer. It is important because:
individual illnesses have knock-on effects on others, it is more complex
managing multiple than single illnesses, and multimorbid patients are heavy
users of medications and health services. Electronic health records (EHRs)
are a good source of information on multimorbidity because they include
information on the same patient over many years. As part of the BIRM-CAM
project, we are developing and applying sophisticated data analysis techniques
to extract relevant information about multimorbidity from EHRs.
We are seeking an ambitious and motivated individual to contribute to the
BIRM-CAM research team. The project will focus on the development and
refinement of models that use EHRs to explore the progression of multi-
morbidities over time, and how clinical outcomes such as mortality and health
service usage may depend on longitudinal trajectories of multi-morbidity.
Relevant modelling techniques include multi-state time-to-event modelling,
prediction modelling, biomarker trajectory modelling and joint modelling.
The successful candidate will have a PhD or equivalent experience in a
strongly quantitative discipline. Past experience with EHRs and/or other "big
data" sources would be highly advantageous, but not essential; training will
be given on the basic concepts necessary to the post. A desire to address
questions of substantive biomedical and societal importance is essential. Good
communication skills and an enthusiasm for collaborating with others
(including non-statisticians) are also essential. Strong programming ability
would be desirable, and experience of computational statistical methods would
be highly advantageous. The successful applicant will be supported in their
career development with a range of formal courses and on-the-job training.
The Unit is actively seeking to increase diversity among its staff, including
promoting an equitable representation of men and women. The Unit therefore
especially encourages applications from women, from minority ethnic groups and
from those with non-standard career paths. Appointment will be made on merit.
We also welcome applications from those wishing to work part-time.
For an informal discussion about this post please contact:
firstname.lastname@example.org or email@example.com.
Fixed-term: The funds for this post are available for 2 years in the first
instance, oor the 31st March 2024, whichever is the earliest.
Click the 'Apply' button below to register an account with our recruitment
system (if you have not already) and apply online.
Closing Date: 14 July 2021
Interview Date: 22 July 2021
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 e-mail address and phone
number, one of which must be your most recent line manager.
Please quote reference SL26907 on your application and in any correspondence
about this vacancy.
The University actively supports equality, diversity and inclusion and
encourages applications from all sections of society.
The University has a responsibility to ensure that all employees are eligible
to live and work in the UK.
MRC Biostatistics Unit
7 June 2021
14 July 2021