Alan Turing Fellow (Population Diversity at Varying Scales)

Alan Turing Fellow (Population Diversity at Varying Scales)

University of

Birmingham, United Kingdom

Post Title: Alan Turing Fellow (Population Diversity at Varying Scales) – 80851
Organisation Advertising Description: College of Medical and Dental Sciences
Location: University of Birmingham
Full time/part time: Full Time
Duration: FTC for up to 24 months
Grade/band: Grade 7 – 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.

The post holder will work with selected collaborators, drawn from the large base of internationally recognised research experts from across the Alan Turing Institute network, to design and implement computational statistical and mathematical methodologies; advancing our understanding of Population-based Biomedical research. The role will require mathematical, statistical and computational modelling skills to make use of complex Biomedical datasets, both quantitative and qualitative. The post holder will use computational skills to implement mathematical and statistical algorithms using modern computer programming languages and to use these to analyse data sets and interpret the results. Strong presentation and communication skills are required to convey complex information to both technical and non-technical experts.

Main Duties
To plan and carry out research, using appropriate methodology and techniques, under the supervision of the Principal Investigator. This may include:
• Developing research objectives and proposals for own or joint research,
• Contribute to writing bids for research funding
• Develop novel methods to represent, compare and analyse Biomedical 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
• Contribute to Centre/Institute research-related activities and administration
• Contribute to enterprise, business development and/or public engagement activities of manifest benefit to the College and the University, often under supervision of a project leader
• Collect research data; this may be through a variety of research methods, such as scientific experimentation, literature reviews, and research interviews

Person Specification

• The candidate should have a first degree and a doctoral (PhD, DPhil) qualification (or be expected to have within 3 months of appointment) in a substantially quantitative discipline (e.g. mathematics, engineering, computer science, physics),
• Substantial experience of mathematical, statistical or computational modelling gained within a research setting,
• Experience of algorithmic development for mathematical and/or statistical computing,
• Expert proficiency in modern low- and high-level programming languages,
• Ability to communicate complex information clearly,
• Experience with the analysis of biomedical data (e.g. electronic health records, genomic data) would be advantageous,
• Ability to assess resource requirements and use resources effectively

Interviews will be held on Wednesday 10th April 2019. Candidates will be asked to give a 10 minute presentation demonstrating their presentation skills and highlighting their current research and how this research would contribute to the ‘Machine Learning for Cancer’ project.

For informal enquiries, please contact Jessica Mylchreest (

Closing date: 05/04/2019

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Quote Reference: 80851