Research Fellow in Data Analytics - Institute of Cancer and Genomic Sciences - 81915 - Grade 7

Summary

Fixed term until December 2026 offering a considerable scope for innovation in the interdisciplinary research. 

The post holder will be part of the Centre for Health Data Science, a hub of collaborative expertise made up of academics and clinicians, focussed on digital epidemiology, clinical bioinformatics, learning health systems, and artificial intelligence for health. Strong links also exist with the Birmingham University Hospitals NHS Trust via the Institute of Translational Medicine.

The purpose of this role is to lead the EU-funded Hypermarker project and interact with other stakeholders across multiple departments. We require applicants with a strong background working with clinical and omics data types, applying statistical and machine learning techniques to identify important associations and interactions between different factors. 

Candidates are expected to have a history of developing models using large data sources and methods (for example: Deep learning, GAN etc), such as UK biobank or other cohorts. The successful applicant will use their computational and statistical expertise to identify novel research opportunities to better understand complex diseases. 

Translational medicine is at the centre of our research, with a focus on providing insights for clinical decision making and developing tools to aid patient wellbeing. The applicant will be involved in the development of these tools, such as prioritizing variants to identify drivers in the multiple diseases using the statistical methods to predict therapeutic responses. This will involve preparation of data through rigorous quality control and gold standard bioinformatics pipelines.

The position requires the ability to independently take responsibility over scientific projects, strong teamwork and communication skills, reliability, attention to detail, and effective time management. Applicants should have a PhD (or near to completion) or equivalent experience in Health Data Science, Computer Science, Biomedical Engineering, Bioinformatics or Computational Biology, including a firm grounding in analysis and integration of big data. Candidates with excellent computational and quantitative skills are encouraged to apply. 

Main Duties

Develop integrative strategies for a diverse set of omics data (metabolomics), integrating the outcomes to investigate complex disease in a multi-omics framework Apply statistical and machine learning and deep learning algorithms to diverse data of different multi omics data sets and quality to identifying associations and causal relationships driving diseases.  Manage and analyse large datasets for analysis using efficient data structures and providing infrastructure for sharing resources. Drive novel applications and take responsibility over large and diverse projects.  Develop research objectives and proposals for own or joint research, with assistance of a mentor if required. Apply knowledge in a way which develops new intellectual understanding. For example, Deep learning-based methods, GAN, generative AI etc.  Disseminate research findings for publication, research seminars etc Supervise students on research related work and provide guidance to PhD students where appropriate to the discipline. Contribute to developing new models, techniques and methods. Collect research data; this may be through a variety of research methods, such as scientific experimentation, literature reviews, and research interviews. Present research outputs, including drafting academic publications or parts thereof, for example at seminars and as posters. Provide guidance, as required, to support staff and any students who may be assisting with the research. Deal with problems that may affect the achievement of research objectives and deadlines. Promotes equality and values diversity acting as a role model and fostering an inclusive working culture.

Person Specification

PhD (or near to completion) in health data science, computer science, artificial intelligence, computational biology, bioinformatics, or similar, or PhD (or near to completion) in a healthcare area with a substantial omics component in their work. Candidates with excellent ML/AI, computational and quantitative skills are encouraged to apply.  Ability to: Demonstrate an understanding of both biomedicine and bioinformatics. Innovate and develop ideas into grant proposals. Learn and keep abreast of latest technological, methodological and software developments. Write concise and timely scientific papers and reports. Plan and prioritise work effectively to meet deadlines. Expertise Scripts in R/Python, especially working with libraries and packages useful for bioinformatics such as the Bioconductor package.  Extensive experience working with omics data and large datasets. Ability to interact with academic and industry partners and explain complex ideas to non-scientists in a comprehensible way.  Ability to work in a heterogeneous environment of diversely skilled individuals. Experience in High Performance Computing facilities and linux systems. Knowledge of the protected characteristics of the Equality Act 2010, and how to actively ensure in day-to-day activity in own area that those with protected characteristics are treated equally and fairly.