Research Associate – Hospital Electronic Health Record data – MRC Biostatistics Unit, Universit[...]

The International Society for Bayesian Analysis; Cambridge; On-site; GBP 30,000 - 40,000; Full time

Job summary

The MRC Biostatistics Unit, part of the University of Cambridge, is offering a Research Associate position focused on developing methodology for Electronic Health Record (EHR) data. The role involves applying advanced statistical methods to enhance the understanding and prediction of patient outcomes through large datasets. Ideal candidates will have a PhD in a quantitative field, strong skills in R, and a willingness to engage in collaborative research efforts within a diverse team environment.

Benefits

Flexible working arrangements

Promotion of diversity and inclusion

Qualifications

• PhD (or close to completion) in a strongly quantitative discipline.
• Experience with high-dimensional, structured data in biostatistics is desirable.
• Strong computational skills, particularly using R.

Responsibilities

• Develop methodology and apply it to EHR datasets.
• Refine research questions and extract relevant data.
• Identify and apply analysis methods for scientific questions.

Skills

Computational skills

Bayesian statistics

Education

PhD in a quantitative discipline

Tools

R

Job description

Research Associate – Hospital Electronic Health Record data – MRC Biostatistics Unit, University of Cambridge

This is an exciting opportunity for an ambitious post-doctoral research associate to join the MRC Biostatistics Unit to carry out research within the Unit’s Precision Medicine theme.

The post-holder will focus on developing novel methodology and applying it to answer clinically-relevant questions, with the aim of improve scientific understanding and/or prediction for hospital patients using large, rich, raw observational clinical informatics datasets extracted from Electronic Health Records (EHR).

A particular focus of this position will be EHR data from Addenbrooke’s hospital, an internationally-renowned teaching hospital in Cambridge. In 2014 was the first UK hospital to implement Epic’s fully electronic health record eHospital system. This provides a single, integrated EHR, with real-time information recorded at the patient’s bedside, including observations, blood tests, procedures and medications. We have several on-going and emerging collaborations with clinicians, clinical scientists and other health care professionals at Addenbrooke’s hospital seeking to improve scientific understanding of their patients and/or prediction of their clinical trajectory to support clinical decision making. The post holder will have the opportunity to take a central role in shaping and refining research questions; extracting and appraising relevant data from the EHR dataset; identifying, developing and applying appropriate analysis methods and tools for answering our collaborators’ scientific questions.

You will have, or be close to completing, a PhD in a strongly quantitative discipline, such as statistics. Prior experience of either applying or developing methodology relating to high-dimensional, structured data in a biostatistical settings is desirable but not essential. Relevant methods include dynamic prediction, dynamic treatment regimes, and time-to-event analyses. Experience of Bayesian statistics is also helpful, but not essential. You will have strong computational skills, particularly using R.

Please contact Robert Goudie with any informal enquiries via email at: [e-mail]

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.

Fixed-term: The funds for this post are available for 2 years in the first instance.

Appointment at Research Associate level is dependent on having a PhD. Those who have submitted but not yet received their PhD will initially be appointed as a Research Assistant (Grade 5, Point 38 £30,497) moving to Research Associate (Grade 7) upon confirmation of your PhD award.

We welcome applications from individuals who wish to be considered for part-time working or other flexible working arrangements.

Closing date for applications is: 3rd January 2022

Interviews are likely to take place early January 2022.

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 must be your most recent line manager.

Please quote reference SL29277 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.