Research Fellow (Statistical Computing) - Cancer and Genomic Sciences

Position Details

Department: Institute of Cancer and Genomic Sciences

Location: University of Birmingham, Edgbaston, Birmingham UK

Full time starting salary is normally in the range £30,395 to £39,609. With potential progression once in post to £42,036 a year.

Grade 7

Full Time / Fixed Term Contract for 3 years

Closing date: 12 September 2019

Interviews will be held on 3 October 2019

Background

This is an exciting and unique opportunity for an ambitious PhD graduate or post-doctoral data scientist with the ability and confidence to lead a strategically important Health Data Research UK Midlands theme in collaboration with the Alan Turing Institute. The post holder will have a background in statistical computing and statistical machine learning and will be responsible for the development of innovative analytical approaches for the discovery of novel endotypes, patterns, and knowledge from patients' health data held in clinical and biomedical environments.

Summary of Role

Fixed term for 3 years offering considerable scope for innovation and academic development.

We are looking to recruit an enthusiastic researcher who will lead the development of novel statistical and AI approaches for the analysis of multimodal medical information residing in clinical and biomedical resources in close collaboration with domain experts.

The post holder will be joining the Gkoutos Group and will be part of the Health Data Research (HDR) UK, situated within the Institute of Translational Medicine and the Centre for Computational Biology. The successful candidate will also be working closely with the Alan Turing Institute. The HDR aims to develop and apply cutting-edge analytical approaches and methodologies in order to address the most pressing health research challenges in the UK. The HDR Midlands provides access to a large variety of multimodal and multidimensional datasets of approx. 5 million patients, including for example more than 20 million clinical text documents and approximately 5 million radiological images and reports.

The purpose of the new role is to lead the development and testing of novel state-of-the-art approaches to extract clinically and biomedical relevant, information and knowledge from patients electronic health records. The post holder will have sound knowledge in the application of statistics and modern machine learning techniques, data science, and a track record in discovering hidden sub-groups/clusters in data. We anticipate that new machine learning and statistical computational approaches will be developed to support this aim. Furthermore, the post holder will have a substantial experience in visualising research outcomes and communicate these to third parties. We offer an excellent network of biomedical and technological collaborations, as well as opportunities for discovery validation and translation into clinic or pharma by domain experts

Applicants should have a PhD or equivalent experience in Computer Sciences, Mathematics, Statistics, or Bioinformatics. Likewise, candidates with a sound and proven Data Science background and excellent quantitative skills are encouraged to apply.

Main Duties / Responsibilities

• Design, create, and apply modern state-of-the-art statistical machine learning and artificial intelligence approaches in biomedical and clinical settings.
• Model and develop statistical models within the context of clinical applications.
• Apply cutting-edge machine learning approaches within a real-world clinical setting in close cooperation with medical experts.
• Drive novel applications and take responsibility over large and diverse projects within the HDR UK and the Alan Turing Institute together with researchers from a variety of different backgrounds.
• Manipulate, integrate, and analyse diverse data of different dimensions and quality, residing in distributed sources.
• Develop research objectives and research proposals.
• Contribute to writing bids for research funding.
• Analyse and interpret data.
• Apply knowledge in a way which develops new intellectual understanding
• 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.
• Undertake management/administration arising from research.
• Contribute to Departmental/School research-related activities and research-related administration.
• Contribute to enterprise, business development and/or public engagement activities of manifest benefit to the College and the University.
• 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.
• Promote equality and diversity values, acting as a role model and fostering an inclusive working culture.

Person Specification

• PhD or equivalent experience in Mathematics, Statistics, Computer Sciences or Bioinformatics with a strong background in statistical computing and statistical machine learning. Candidates from related disciplines with a sound and proven background in these and excellent quantitative skills are encouraged to apply.
• A relevant degree, at a minimum of a 2:1 classification or equivalent is required.
• Ability to:

o Demonstrate an understanding of both science and informatics.

o Innovate and develop ideas into grant proposals.

o Learn and keep abreast with the latest technological, methodological and software developments.

o Write concise and timely scientific papers and reports.

o Plan and prioritise work effectively to meet deadlines.

• Proven and extensive experience within the field of statistical computing and
• Good presentation skills and talent for technology and knowledge transfer.
• 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.
• Proficiency in modern programming languages (e.g. R, Python, Java, Groovy), strong background in applying relevant statistical libraries, and database design and handling.
• 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.

Informal enquiries can be sent to CCB Centre Manager, Jessica Mylchreest, j.mylchreest@bham.ac.uk , Telephone +44 (0)121 414 7012.