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Job id: 078846. Salary: £42,405 – £49,785 per annum, including London Weighting Allowance.

Posted: 13 November 2023. Closing date: 11 December 2023.

Business unit: Faculty of Life Sciences & Medicine. Department: Department of Women & Children's Health.

Contact details: Lucilla Poston.

Location: Guy's Campus. Category: Research.

Job Description

About Us: The Department of Women’s & Children’s Health in King’s College London is a leading research institution dedicated to advancing the understanding of maternal and child health. The GEN2020 project utilises the analysis of National Health Service (NHS) electronic health records (EHR) to explore the life course of health and disease in pregnancy, particularly in the multi-ethnic inner-city populations of South London. We are currently seeking a dedicated Research Assistant/Associate in Statistics to join our dynamic and expanding research team.

Position Overview: You will play a crucial role in our research project GEN2020, led by Professor Grainne McAlonan. This study investigates the early outcomes of children who were in utero during the COVID-19 pandemic including those who were exposed to maternal SARS-CoV-2 virus infection during prenatal life. This will include the linkage of routinely collected and enriched early years health and development data held within Elixir to government held education and social care data from pre-pandemic (reference) and pandemic periods. You will support the creation, curating and analysis of these unique datasets and create an imporant data resource for scientists to use both now and for the future.

The post will involve managing health and social data linkage. You will be leading on the data linkage process by which health data from different sources are linked to GEN2020 research in a way that protects confidentiality, maintains security and improves the quality of data whilst maximising potential secondary uses of pseudonymised clinical data for improved research benefits. 

The successful candidate will also have the opportunity to be an author on all relevant academic publications resulting from the research. You will be an integral part of the multidisciplinary efforts of the Gen2020 programme which brings together preclinical and clinical neurosciences and child health investigators to understand the earliest determinants of childhood outcomes. 

This post will be offered initially on an a fixed-term contract untill  Febuary 2025.

Key responsibilities

  • To undertake Gen2020 study analyses of cognitive development and function in children (up to 3years of age) early outcomes of children who were in utero during the COVID-19 (with reference to a non-pandemic cohort) 
  • Conduct statistical analysis of existing EHR from our multi-ethnic inner-city population, with particular use of longitudinal modelling. 
  • Working with the PI to obtain essential approvals from relevant bodies including Research Ethics and Health Research Authority (HRA) Confidentiality Advisory Group (CAG) Section 251 approval.
  • To maintain an up-to-date technical knowledge of data linkage methodology, including deterministic and probabilistic matching, to carry out linkages and data extraction in a relational database and to understand the impact of linkage error associated with different linkage methodologies; to lead on work to establish the effect of linkage error on the specific linkages conducted within the project.
  • To be responsible for managing administrative tasks, including receiving and handling large volume datasets via Secure File Transfer Protocol (SFTP) with complex and sensitive information from Kings Health Partners, the BRC, and other national and international organisations.
  • To manage the resolution of technical system and dataset integration issues; to lead on the development of standards and methods for data mining, coding and analysis and to manage data extraction services.
  • To be aware of key legislation in relation to data linkage (e.g., GDPR); and to be responsible for and implement quality and efficiency improvement initiatives for the GEN2020 team 
  • Collaborate with other team members to produce high-quality academic research outputs.
  • Attend and present findings at research meetings and conferences.

The above list of responsibilities may not be exhaustive, and the post holder will be required to undertake such tasks and responsibilities as may reasonably be expected within the scope and grading of the post.

Skills, knowledge, and experience

Essential criteria

  1. A Ph.D. or Master’s degree and equivalent experience in Statistics, Biostatistics, Epidemiology, or a related field
  2. Hands on experience of constructing linked clinical datasets using relational databases, with proficiency in relational database software (e.g SQL).
  3. Strong quantitative and analytical skills of large-scale health related data, using statical software packages (e.g., R, Python, or STATA).
  4. First-hand experience of relevant approval processes e.g. section 251, research ethics 
  5. Knowledge of the General Data Protection Regulations (GDPR), Digital Economy Act, and working within NHS Information governance standards.
  6. Excellent communication and teamwork abilities.
  7. Highly organized and detail-oriented project management skills 
  8. Ability to act on own initiative.
  9. Proactive team player able to respond to tight deadlines.
  10. Committed to equality, diversity, and inclusion, actively addressing areas of potential bias.

Desirable criteria

  1. Knowledge of publicly available health, social and mapping data from e.g., NHS Digital, NHSE/I, PHE, ONS, etc.
  2. Experience of working within the ONS Secure Research Service environment
  3. Knowledge of clinical phenotyping codes such as Read Codes and SNOMED.
  4. Able to adapt and incorporate new data science approaches into complex database analysis.
  5. A passion for contributing to meaningful research in maternal and child health

Candidates are strongly encouraged to specifically address the essential criteria outlined in the Person Specification in their covering letter.