Imperial College London
Job Description
Job Title:
Research Assistant/Associate
Section:
Division of Infectious Diseases/Neonatal Medicine &
Department of Primary Care and Public Health
Department:
Department of Medicine &
School of Public Health
Job Family/Level:
Academic and Research / Level A or B
Salary:
Level A: (Research Assistant) £28,770 - £31,880 per annum
Level B: (Research Associate) £32,750 - £33,590 per annum
Responsible to:
Professor Neena Modi/Professor Azeem Majeed
Key Working
Relationships:
Academic and research staff working within the Neonatal Data
Analysis Unit and the School of Public Health
Location:
Chelsea & Westminster and Charing Cross Campuses
Contract:
Full time, fixed term for 12 months.
Summary
This post is a component of a NIHR programme grant in neonatal research, “Medicines for
Neonates: using routinely collected NHS electronic clinical data for applied research to
improve new-born outcomes”, led by Professor Neena Modi, Professor of Neonatal
Medicine. The project falls is supported by the Northwest London Collaboration for Applied
Health Research and Care (CLAHRC) programme.
The appointee will work with a multidisciplinary team that includes specialists in
epidemiology, applied statistics, neonatology and primary care. The epidemiological
supervisors will be Dr Sonia Saxena, and Professor Azeem Majeed, and the neonatal
supervisor Professor Neena Modi.
This is an exciting opportunity for a suitable candidate with a Masters/PhD in a relevant
area (eg Statistics, Mathematics, Epidemiology, Public Health). You will have experience in
the use of large datasets, and their linkage. You will determine long term clinical outcomes
in preterm neonates using neonatal data (the National Neonatal Research Database) linked
to hospital admission data (Hospital Episodes Statistics).
This is a full-time position for 12 months in the first instance and subject to probationary
review after 3 and 6 months. You will be based primarily at the Chelsea & Westminster
campus of Imperial College London in the Section of Neonatal Medicine as a member of
the Department of Medicine but will also travel as appropriate to the Department of Primary
Care and Public Health, School of Public Health at Imperial College London Charing Cross
Campus. You will be expected to play a full and active role in the academic life of the
Divisions/Departments.
Background: Longitudinal outcomes of being born preterm are not captured
systematically because of the logistical difficulties and costs of long term follow-up and
poor recording of early life exposures in retrospective studies. Linkage between healthcare
databases is a fundamental new initiative which utilises existing routinely available
electronic patient record data with the long-term aim of improving patient healthcare. The
NHS is in a unique position to examine population-based neonatal outcomes beyond
discharge from a neonatal unit. Pilot work in this area has enabled us to develop a
neonatal birth cohort that is now fit for purpose to begin this important work.
Aims: To link clinical datasets to examine long term clinical outcomes in preterm babies
Design: Birth cohort study using linked National Neonatal Research Database & HES
datasets.
Outcomes: Hospital admissions for subsequent major diagnoses in acute and chronic
childhood conditions, and subsequent mortality.
Methods: Data are routinely captured in electronic patient records on infants admitted to
NHS neonatal units, and held in the National Neonatal Research Database. Hospital
Episodes Statistics contain information on all admissions to NHS hospitals. Personal
identifiers allow individual patient episodes to be linked to create a long-term clinical
history. This study will allow us to examine longer term health outcomes in preterm infants,
and investigate rates of hospitalisation, and in-hospital and subsequent mortality, by age,
sex, region, socio-economic status and ethnicity. The findings of this study have the
potential to fill a major gap in the field of neonatal medicine and life course epidemiology.
Key Responsibilities
This job description is intended to be a general guide to the duties and responsibilities of
the post and will be reviewed as necessary to meet the developing needs of the Unit and its
work. However the key responsibilities will be:
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To carry out linkage between the National Neonatal Research Database and HES
data
To examine data completeness and quality
To interrogate the linked datasets to ascertain later outcomes of preterm babies
General responsibilities
 To maintain accurate and complete records
 To work closely with other members of the research group
 To report regularly to supervisors
 To contribute to the intellectual life of the Department
 To contribute to the preparation of manuscripts for publication
 To keep up-to-date with publications and advances in the field
 To assist in the timely execution of this project
 To undertake any necessary training and/or development
 To observe and comply with all College policies and regulations, including the key policies
and procedures on Confidentiality, Conflict of Interest, Data Protection, Equal
Opportunities, Financial Regulations, Health and Safety, Imperial Expectations (for new
leaders, managers and supervisors), Information Technology, Private Engagements and
Register of Interests, and Smoking.
 To undertake specific safety responsibilities relevant to individual roles, as set out on the
College Website Health and Safety Structure and Responsibilities page
(http://www3.imperial.ac.uk/safety/policies/organisationandarrangements).
 Any other duties commensurate with the grade of the post as directed by line
manager/supervisor
Appointment as Research Associate to include (in addition to above):
 To assist in the preparation of applications for further funding
 To contribute to peer-reviewed publications
 To take initiatives in the planning of research
 To provide guidance to undergraduate, graduate and PhD Students
 To contribute to other duties commensurate with the grade of the post as directed by your
line manager/supervisor
As this post is exempt from the Rehabilitation of Offenders Act 1974, a satisfactory
(standard/enhanced/enhanced for regulated activity) Disclosure and Barring Service check
will be required for the successful candidate. Further information about the DBS disclosure
process can be found at http://www.homeoffice.gov.uk/agencies-public-bodies/dbs/ or by
telephoning 0870 90 90 811. You may also wish to view the College’s policy statements on
the Recruitment and Employment of Ex-Offenders and the Secure Storage, Use, Retention
& Disposal of Disclosures and Disclosure Information.
Job descriptions cannot be exhaustive and the post-holder may be required to
undertake other duties, which are broadly in line with the above key responsibilities.
Imperial College is committed to equality of opportunity and to eliminating
discrimination. All employees are expected to adhere to the principles set out in its
Equal Opportunities in Employment Policy, Promoting Race Equality Policy and all
other relevant guidance/practice frameworks.
Imperial College London
Person Specification
Applicants are required to demonstrate that they possess the following attributes:
Imperial Expectations
These are the 7 principles that Imperial leaders, managers and supervisors are expected to
follow:
1) Champion a positive approach to change and opportunity
2) Communicate regularly and effectively within, and across, teams
3) Consider the thoughts and expectations of others
4) Deliver positive outcomes
5) Encourage inclusive participation and eliminate discrimination
6) Support and develop staff to optimise talent
7) Work in a planned and managed way
Education and Qualifications
Essential for appointment as Research Assistant
 MSc or equivalent in Statistics, Mathematics, Epidemiology, Public Health or
other relevant discipline
Essential for appointment as Research Associate
 PhD or equivalent in Statistics, Mathematics, Epidemiology, Public Health or
other relevant discipline
Experience and Knowledge
Essential
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Experience of working with large datasets and data linkage
Ability to interrogate large datasets
Familiarity with public health, neonatal services or other relevant fields
Proven ability to analyse complex sets of quantitative data
Proven ability to write clearly for a variety of audiences
Experience of working in office based settings
Experience of working in a team
Experience of working to targets
Essential for appointment as Research Associate (in addition to above)
 Substantial experience in the use of large datasets
 Track record of successful research in public health, neonatal services or other
relevant fields
 Experience in the management and analysis of complex data
 Record of publications in peer-reviewed journals
Competencies, Skills and Abilities
Essential
 Experience in SAS, Stata or other equivalent software
 Excellent IT skills, including proficiency in Microsoft Word, Access, Excel and
Outlook
 Excellent communication and presentation skills, both oral and written
 Ability to work to deadlines
 Good, proven interpersonal skills and the ability to deal with a wide range of people
in an appropriate manner
 Ability to write reports in a clear and concise manner
 Excellent attention to detail and commitment to scholarship
 Ability to work constructively and effectively within a team
 Ability to work independently and use own initiative
 Ability to prioritise a varied workload and work under pressure to meet deadlines
while maintaining a high level of accuracy
Personal Attributes
Essential
 Willingness to undertake any necessary training for the role
 Willingness to travel to different locations for work as needed
 An open, flexible and positive approach to working in a constantly changing
environment
 Discipline and regard for confidentiality and security at all times