JiscMail Logo
Email discussion lists for the UK Education and Research communities

Help for ALLSTAT Archives


ALLSTAT Archives

ALLSTAT Archives


allstat@JISCMAIL.AC.UK


View:

Message:

[

First

|

Previous

|

Next

|

Last

]

By Topic:

[

First

|

Previous

|

Next

|

Last

]

By Author:

[

First

|

Previous

|

Next

|

Last

]

Font:

Proportional Font

LISTSERV Archives

LISTSERV Archives

ALLSTAT Home

ALLSTAT Home

ALLSTAT  November 2019

ALLSTAT November 2019

Options

Subscribe or Unsubscribe

Subscribe or Unsubscribe

Log In

Log In

Get Password

Get Password

Subject:

Reminder: PhD on trials methodology at Exeter: One week til deadline

From:

Jack Bowden <[log in to unmask]>

Reply-To:

Jack Bowden <[log in to unmask]>

Date:

Mon, 25 Nov 2019 10:24:54 +0000

Content-Type:

text/plain

Parts/Attachments:

Parts/Attachments

text/plain (48 lines)

Dear Allstat

Please see below for details of a 3-year fully-funded PhD studentship to develop statistical methods for the analysis of trial data at the University of Exeter. Stipends are at an enhanced rate of £17,059 (2020-21) and all Home/EU tuition fees are covered. Funds will also be available for travel and research costs.

Please contact the primary supervisor (Jack Bowden: [log in to unmask]) for further information & follow the link below to apply

http://www.exeter.ac.uk/studying/funding/award/?id=3753

Closing date: 2nd December 2019

PhD title: Exploiting observational data in the design and analysis of clinical trials into effective diabetes treatment. 

Supervisors:

Prof Jack Bowden, College of Medicine and Health, University of Exeter  ([log in to unmask]) and University of Bristol
Dr  Beverley Shields, College of Medicine and Health, University of Exeter
Dr Lauren Rodgers,College of Medicine and Health, University of Exeter

Location: University of Exeter Medical School, RILD Building, RD&E Hospital Wonford, Barrack Road, Exeter, EX2 5DW

Project Summary: This studentship will develop novel methods to exploit observational study and patient record data to improve the design and analysis of clinical trials into Diabetes. The student will develop strong quantitative skills in Statistics & data science, as well as state-of-the-art knowledge of Diabetes, its causes consequences, and its effective treatment.

Project Description

In diabetes, there are many different treatment options, but little guidance regarding which drug works best for which individuals.  As part of our precision medicine research, we are developing statistical models to help determine the optimal treatment for diabetes patients based on their clinical features such as age, BMI and blood biomarkers.

To develop these models, we have been using data from large GP records databases and randomised controlled trials (RCTs), but both have limitations. In RCTs, patients tend to reflect a narrow, selected subgroup and not all patients adhere to the study protocol or may drop out before study completion. This hinders the interpretation and generalisability of a trial’s findings in the outside world.  In contrast, observational data such as GP records have real-world relevance, but the data are messy, and many variables must be controlled for to obtain estimates comparable to those from an RCT.

Despite these challenges, there is a growing interest in developing statistical methods to combine both data sources, in order to improve patient care. This PhD will explore three specific aims: 
1) To develop causal inference approaches for combining observational and RCT data to improve treatment effect estimation in a trial.
2) To use these findings to further refine our treatment prediction algorithms.
3) To test updated algorithms in trial settings, incorporating real world data to further improve trial analysis and better reflect routine practice.
This PhD will offer the student the opportunity to work with leading statisticians in trial methodology and a world-renowned diabetes research team.

The student should have a solid grounding in Statistics and experience in handling and analysing medical data. The student will join a vibrant, diverse and world class interdisciplinary research team, including geneticists, biological scientists, mathematicians, computer scientists and clinicians, all studying aspects of diabetes and related conditions.

Entry requirements
Applicants should have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK.   Applicants with a Lower Second Class degree will be considered if they also have Master’s degree.  Applicants with a minimum of Upper Second Class degree and significant relevant non-academic experience are encouraged to apply.
Applicants must ensure that they meet the eligibility requirements of the University of Exeter.  To qualify for ‘home’ tuition fee status, you must be a UK or EU citizen who has been resident for 3 years prior to commencement.

All applicants would need to meet our English language requirements by the start of the project http://www.exeter.ac.uk/postgraduate/apply/english/.

You may leave the list at any time by sending the command

SIGNOFF allstat

to [log in to unmask], leaving the subject line blank.

Top of Message | Previous Page | Permalink

JiscMail Tools


RSS Feeds and Sharing


Advanced Options


Archives

April 2024
March 2024
February 2024
January 2024
December 2023
November 2023
October 2023
September 2023
August 2023
July 2023
June 2023
May 2023
April 2023
March 2023
February 2023
January 2023
December 2022
November 2022
October 2022
September 2022
August 2022
July 2022
June 2022
May 2022
April 2022
March 2022
February 2022
January 2022
December 2021
November 2021
October 2021
September 2021
August 2021
July 2021
June 2021
May 2021
April 2021
March 2021
February 2021
January 2021
December 2020
November 2020
October 2020
September 2020
August 2020
July 2020
June 2020
May 2020
April 2020
March 2020
February 2020
January 2020
December 2019
November 2019
October 2019
September 2019
August 2019
July 2019
June 2019
May 2019
April 2019
March 2019
February 2019
January 2019
December 2018
November 2018
October 2018
September 2018
August 2018
July 2018
June 2018
May 2018
April 2018
March 2018
February 2018
January 2018
December 2017
November 2017
October 2017
September 2017
August 2017
July 2017
June 2017
May 2017
April 2017
March 2017
February 2017
January 2017
December 2016
November 2016
October 2016
September 2016
August 2016
July 2016
June 2016
May 2016
April 2016
March 2016
February 2016
January 2016
December 2015
November 2015
October 2015
September 2015
August 2015
July 2015
June 2015
May 2015
April 2015
March 2015
February 2015
January 2015
December 2014
November 2014
October 2014
September 2014
August 2014
July 2014
June 2014
May 2014
April 2014
March 2014
February 2014
January 2014
December 2013
November 2013
October 2013
September 2013
August 2013
July 2013
June 2013
May 2013
April 2013
March 2013
February 2013
January 2013
December 2012
November 2012
October 2012
September 2012
August 2012
July 2012
June 2012
May 2012
April 2012
March 2012
February 2012
January 2012
December 2011
November 2011
October 2011
September 2011
August 2011
July 2011
June 2011
May 2011
April 2011
March 2011
February 2011
January 2011
December 2010
November 2010
October 2010
September 2010
August 2010
July 2010
June 2010
May 2010
April 2010
March 2010
February 2010
January 2010
December 2009
November 2009
October 2009
September 2009
August 2009
July 2009
June 2009
May 2009
April 2009
March 2009
February 2009
January 2009
December 2008
November 2008
October 2008
September 2008
August 2008
July 2008
June 2008
May 2008
April 2008
March 2008
February 2008
January 2008
December 2007
November 2007
October 2007
September 2007
August 2007
July 2007
June 2007
May 2007
April 2007
March 2007
February 2007
January 2007
2006
2005
2004
2003
2002
2001
2000
1999
1998


JiscMail is a Jisc service.

View our service policies at https://www.jiscmail.ac.uk/policyandsecurity/ and Jisc's privacy policy at https://www.jisc.ac.uk/website/privacy-notice

For help and support help@jisc.ac.uk

Secured by F-Secure Anti-Virus CataList Email List Search Powered by the LISTSERV Email List Manager