Postdoctoral Research Associate in Machine Learning

Queen Mary University of London; London; On-site; GBP 35,000 - 45,000; Full time

Job summary

A leading educational institution in London seeks a Postdoctoral Research Associate in Machine Learning to enhance the understanding and management of anemia. The role involves developing machine learning models using electronic health record data, within an ambitious international research team. Ideal candidates will have a PhD and relevant experience in machine learning methodologies. Competitive salary and extensive professional development opportunities are offered.

Benefits

Competitive salary

Generous pension scheme

30 days' leave per annum

Season ticket loan scheme

Flexible working arrangements

Qualifications

• Experience with large-scale electronic health record data.
• Knowledge of machine learning model development.
• Understanding of diverse and admixed populations in healthcare.

Responsibilities

• Develop machine learning models for blood disorder diagnosis.
• Leverage electronic health record data for research projects.
• Integrate research with multidisciplinary teams.

Skills

Machine learning

Federated learning methodology

Data analysis

Education

PhD in a relevant field

Job description

Overview

We have an opportunity for a Postdoctoral Research Associate in Machine Learning to join PHURI, within the research team of Dr Joseph Taylor working on improving our understanding and management of anemia, a leading causes of morbidity and mortality globally. The postholder will be part of the international BloodCounts! Consortium, a collaborative network of partners across multiple UK (Queen Mary University of London, University of Cambridge, University College London, NHS Blood and Transplant) and international sites (including VU Amsterdam, KU Leuven, MRC Gambia, Apollo Hospitals India). It is at the forefront of Federated Learning in healthcare and is focused on improving diagnosis and understanding of diseases with a signature in the blood.

Responsibilities

• The successful candidate will deliver projects that leverage large-scale electronic health record data and rich cytometry data derived from full blood count analysers to develop and refine machine learning models to improved the diagnosis of common blood disorders in diverse and admixed populations.
• They will have experience and knowledge of machine learning and federated learning methodology.
• They will also have the opportunity to integrate their research with other thematic foci for PHURI in our multidisciplinary institute.
• We are an ambitious, curious and enthusiastic international team, that promotes scientific excellence and career development in the context of happy family and other demands.

About PHURI

The Precision Healthcare University Research Institute (PHURI) aims to improve health through data-driven medicine. PHURI's multidisciplinary teams will address interconnected research themes including Omics Science; MedTech and Devices and Therapeutic Innovation - transcending the existing boundaries between disciplines.

Research themes and impact

These themes will come together to create a complete journey from disease identification, through to translation with the development of therapies, devices or clinical intervention to ensure we improve disease prediction, personalisation of treatment and disease management and prevention to improve patient outcomes. This integrated approach is a distinguishing feature of PHURI in which we use our linked health and molecular patient data to develop innovative technologies that will transform existing care pathways.

About Queen Mary

At Queen Mary University of London, we believe that a diversity of ideas helps us achieve the previously unthinkable.

Throughout our history, we\'ve fostered social justice and improved lives through academic excellence. And we continue to live and breathe this spirit today, not because it\'s simply 'the right thing to do' but for what it helps us achieve and the intellectual brilliance it delivers.

We continue to embrace diversity of thought and opinion in everything we do, in the belief that when views collide, disciplines interact, and perspectives intersect, truly original thought takes form.

We offer competitive salaries, access to a generous pension scheme, 30 days' leave per annum (pro-rata for part-time/fixed-term), a season ticket loan scheme and access to a comprehensive range of personal and professional development opportunities. In addition, we offer a range of work life balance and family friendly, inclusive employment policies, campus facilities and flexible working arrangements.