Statistician/Machine learning Engineer/Data Analys...

Applications are invited for a Statistician/Machine learning Engineer/Data Analyst to join the fast-growing Haematology Data Science Initiative (HDSCI), which comprises two major research projects Haem-Match (www.haemmatch.org) and BloodCounts! (www.bloodcounts.org).

Candidates should have a degree or equivalent experience or qualification in Informatics or Software Engineering, Mathematics, Computer Science or Systems Engineering at Bachelor level. They should also have experience of database and data warehouse design, experience of preparing detailed technical documentation, and knowledge of data modelling. Experience of managing large heterogenous datasets, experience with data analysis, hypothesis testing and algorithm evaluation essential.

The post holder will be working within the Clinical Research Informtics Unit (CRIU) which has also established collaborations with the Alan Turing Institute and Health Data Research UK, among others. This milieu will allow the post-holder to gain exposure to broad aspects of data science, both operational and research, including electronic health records, -omics, imaging, wearables, natural language processing, machine learning, artificial intelligence, and information governance.

The HDSCI project, coordinated through University of Cambridge, UCLH BRC, NHS Blood and Transplant and part of a larger international collaboration, is embedded in the CRIU and the postholder will be a member of the multidisciplinary HDSCI team, which includes clinical bioinformaticians, experts in statistical genomics, blood cell immunogenicity and randomised controlled trials, clinical haematologists caring for patients with inherited anaemias, and researchers in Artificial Intelligence & Machine Learning (AI&ML).

BloodCounts! Brings Together a Network Of Experts Across Clinical, Quantitative Science And Corporate Enterprises To Apply Artificial Intelligence To Analyse Routine Clinical Haematology Data And Turn Them Into a Broad Surveillance Network To Detect Infectious Disease Outbreaks Without The Need For Any New Instruments Or Reagents. The Post Holder Will

• Consolidate receive, decrypt and QC data necessary for the project.
• Apply AI&ML to Full Blood Count (FBC) results with the aim of discovering signatures of important medical conditions (e.g., viral infection [incl. SARS‑ CoV‑ 2], iron-deficiency anaemia vs thalassaemia trait, thrombotic thrombocytopenic purpura and haemolytic uraemic syndrome, inherited haematological disorders),
• Integrate polygenic scores for blood cell traits into FBC results reports with the aim of enhancing the diagnostic value of this test, which in the UK is applied to approximately 100 million samples per year.
  
  

University College London Hospitals NHS Foundation Trust (UCLH) is one of the most complex NHS trusts in the UK, serving a large and diverse population. We provide academically led acute and specialist services, to people from the local area, from throughout the United Kingdom and overseas. Our vision is to deliver top-quality patient care, excellent education, and world-class research.

We provide first-class acute and specialist services across eight sites:

• University College Hospital (incorporating the Elizabeth Garrett Anderson Wing)
• National Hospital for Neurology and Neurosurgery
• Royal National ENT and Eastman Dental Hospitals
• University College Hospital Grafton Way Building
• Royal London Hospital for Integrated Medicine
• University College Hospital Macmillan Cancer Centre
• The Hospital for Tropical Diseases
• University College Hospital at Westmoreland Street
  
  

We are dedicated to the diagnosis and treatment of many complex illnesses. UCLH specialises in women’s health and the treatment of cancer, infection, neurological, gastrointestinal and oral disease. It has world class support services including critical care, imaging, nuclear medicine and pathology.

We are committed to sustainability and have pledged to become a carbon net zero health service, embedding sustainable practice throughout UCLH. We have set an ambitious target of net zero for our direct emissions by 2031 and indirect emissions by 2040.

For further details / informal visits contact: Name: Rhonda Henley-Smith Job title: NIHR BioResource @UCLH Manager Email address: rhonda.henley-smith@nhs.net